November 6, 2015 Conference paper Open Access

Bui, Nicola; Malanchini, Ilaria; Widmer, Joerg

MARC21 XML Export

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    <subfield code="a">Prediction, Resource Allocation</subfield>
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    <subfield code="a">Admission Control</subfield>
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    <subfield code="u">Bell Labs, Alcatel-Lucent</subfield>
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    <subfield code="u">https://zenodo.org/record/51786/files/Anticipatory_Admission_Control_Resource_Allocation_2015_EN.pdf</subfield>
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    <subfield code="u">IMDEA Networks Institute, UC3M, Leganes</subfield>
    <subfield code="a">Bui, Nicola</subfield>
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    <subfield code="a">Anticipatory Admission Control and Resource Allocation for Media Streaming in Mobile Networks</subfield>
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    <subfield code="a">Academic Free License v3.0</subfield>
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    <subfield code="a">&lt;p&gt;The exponential growth of media streaming traffic will have a strong impact on the bandwidth consumption of the future wireless infrastructure. One key challenge is to deliverservices taking into account the stringent requirements of mobile video streaming, e.g., the users&amp;rsquo; expected Quality-of-Service. Admission control and resource allocation can strongly benefit from the use of anticipatory information such as the prediction of future user&amp;rsquo;s demand and expected channel gain. In this paper, we use this information to formulate an optimal admission control scheme that maximizes the number of accepted users into the system with the constraint that not only the current but also the expected demand of all users must be satisfied. Together with the optimal set of accepted users, the optimal resource scheduling is derived. In order to have a solution that can be computed in a reasonable time, we propose a low complexity heuristic. Numerical results show the performance of the proposed scheme with respect to the state of the art.&lt;/p&gt;</subfield>
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    <subfield code="a">10.1145/2811587.2811604</subfield>
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