O

ABSTRCT


INTRODUCTION
Cloud Computing technology maintain data and application using central remote server. It permit the user to use thesetechnologies without installation their related files at any computer. At any time resources and applications are available to be use from the cloud via the internet. Cloud technology is the base of new business. Cloud technology are taking advantage of economies of scale and multi tenancy which are used to decrees the cost of information technology resources. However, data use a significant and growing portion of energy, an average data consumes as much energy as 30,000 households. Thecurrent demand of cloud computing technology is that consumer only used those data which they required, and only pay for what they actually consume. Mobile computing is an interaction between human and computer by which computer is expected to be transported during usage [4]. It includes mobile hardware, mobile communication n mobile software [4]. The greatest feature of the mobile cloud computing is that it allows user to connect its relevant data from anywhere in the world via network. Energy-aware computing is crucial for cloud computing systems that consume considerable amount of energy [5]. Problems occur when trying to support mobility in computing devices: resource sparseness, hazardousness, finite energy source, and low connectivity [5].
In this paper we refer job sharing/scheduling based algorithm so that each connected devices gets their part of work and using offloading process each one can do their work properly & acknowledges to the central server. By using of Service Level Agreement, achieving high [35] performance in cloud computing and of great significance for improving resource load balance, security, reliability and reducing energy consumption of the whole system.[32,35In this paper we used Wi-Fi as connectivity option. Using Wi-Fi based architectural framework we can utilize all the global resources via network connectivity but not only limited to the local resources. Cloud is available for low end mobile device as well as high end mobile device in this framework. Most of the cloud resource would be mobile, computer, laptop etc. Dynamic mobile cloud framework can handle run time resources and connectivity. In the framework we explain vision towards the process large amount of job which requires huge hardware resources with smart phones by partitioning the task into the number of jobs which is cost-saving, battery-life saving. Using this architectural framework huge task can be done in just a matter of time using global resources.

RESEARCHD ETAILS
Now days,Cloud Computing is one of the most famous topic and it is play very important role in enterprises due to the cost charges and computational promises it gives. I am doing the study on the issue of "Opportunistic Job Sharing For Mobile Cloud Computing" Opportunistic Job Sharing group is an enterprise which is using Cloud Computing andmy research question are: What are the basicprofits and drawback regarding cost, time and data security by using Wi-Fi technic for Enterprises to adopt Cloud Computing?

2.1Purpose of Research
Basic fundamental of the thesis is to extract the advantages and drawbacks with respect to cost, time, datasecurity and data availability so organizations can have by the use of Cloud Computing for the implementation of their information system. Finally concluding the factors in terms of cost, time and data security by using Wi-Fi technic, enterprises should keep in mind while adopting CC for the effective and efficient use of their information system.

Related Work
In this section we provide a review of related research efforts, ranging from the earlier approaches that focus two methods relating to offloading, job scheduling work from mobile.
Marinelli [2] introduce Hyrax, mobile cloud computing technology consumer that agrees mobile devices to utilize cloud computing platforms. Based on Hadoop1, the main focus of this work is to port a client into a mobile device to enable the integration. The author introduces the concept of using mobile devices as resource providers, but further experimentation is not included. [2] Integration between mobile devices and cloud computing is presented in several previous works. Christensen [1] presents general requirements and key technologies to achieve the goal of mobile cloud computing. The author introduces an exploration on latest smart phones, framework awareness, cloud and restful based web services, and explains how to create this innovative components for a better experience for mobile phone users. [1] Fernando, W. Loke and WennyRahayu, Introduce the feasibility of a mobile cloud computing framework to use local resources [4]. Main aim of the framework is to determine a usefulness of sharing workload at runtime. The results of experiments conducted with Bluetooth transmission. [4] RehanSaleem (831015-T132),It Introduce cloud computing's effect on enterprises, theirresearch work is define, How to handle the effects of Cloud Computing in the enterprises. The specific areas he researched during his study were cost and security and specially he give the differences between grid computing and cloud computing, Cloud Computing is the sum of Software as a Service (SaaS) and Utility Computing, but does not include Private Clouds. [6] PriyankaGupta&PoojaDeshpande, It introduceto Efficient Resource Allocation and Scheduling Approach to Enhance the Performance of Cloud Computing [32].Attempts to schedule the jobs such a way that cloud provider can gain maximum benefit for his service and Quality of Service (QoS) requirement user's job which enhances the performance of cloud service. [32]

Motivation forthe Work
Let's consider the scenario of Mr Rahul (Photo editor) travelling by car. He suddenly gets an email to edit a large size image. He starts editing. Since the large size image need to be edited only on laptop because it cannot be edited on the smart phones due to memory constraints, limited battery power & low CPU processing of smart phones. As the matter of the fact he cannot edit the image.
In this scenario if he has a dynamic mobile cloud computing framework through this he can create a cloud using network (Wi-Fi) then the result would be different. He uploads image to the central server (cloud) using Wi-Fi network & asks some of his colleagues to do it. All the cloud clients (colleagues) edit the particular part of the image and again send back the response to the server. Central server processes all the responds and again sends back to the Rahul.
In this way Rahul explores the dynamic architectural framework by using sharing/offloading process to complete his job and moved over four major challenges: reduce bulkiness, time-saving, limited memory and battery power. Now John is still available to do any urgent work which is the best part of using this framework.

THEORETICAL DETAILS
Main idea of this section is to introduce the framework of my research thesis.

DEFINITION
There are lots of definitions of Cloud Computing giving by different-different researchers. Barkley RAD defines Cloud Computing as [6]: "Cloud Computing refers to both the applications as services over the Internet and the hardware and systems software in the datacentres that provide those services. The services themselves have long been referred to as Software as a Service (SaaS). The datacentre hardware and software is what we will call a Cloud. When a Cloud is made available in a pay-as-you-go manner to the general public, we call it a Public Cloud; the service being sold is Utility Computing. We use the term Private Cloud to refer to internal datacentres of a business or other organization, not made available to the general public. Thus, Cloud Computing is the sum of SaaS and Utility Computing, but does not include Private Clouds. People can be users or providers of SaaS, or users or providers of Utility Computing." [6] Cloud Computing is a new addingpattern. Infrastructure resources (hardware, storage and system software) and applications are provided in as-a-Service manner. When these services are offered by an independent provider or to external customers, Cloud Computing is basically based on fundamental of paid-per-use concept. Main features of Clouds are virtualization and dynamic scalability on demand. Utility computing technology and software as a services are provided in acombinedstyle, whereas utility computing might be consumed separately. Cloud services are used up either via Web browser or Application programming interface. [33]

3.2Cloud Service Models
There are 3 Cloud Services Models which are explain below • Cloud Software as Service: -It is also known as "On demand Software"and it is a software licensing and it provide the software to consumer on subscription base.
• Cloud Platform as Service:-In this type of service, the consumer can deploy, the user generated or developed applications which is create by using programming or tools given by provider, on the cloud infrastructure. [6] • Cloud Infrastructure as Service: -This is a capability provided to the consumer by which, it can provision processing, storage, networks and other fundamental computing resources where the consumers can deploy and run the software.

Cloud Deployment Models
• Public Cloud:-This public cloud is available for every organization.
• Private Cloud:-This cloud is available only for particular organization or company.
• Community Cloud: -In this type of cloud deployment model, the infrastructure of the cloud system is commonly used by many of the organizations and supports a specific community with shared concerns.
• Hybrid Cloud:-It is a composition of two or more different clouds that is private or community or public. Element of the hybrid cloud are tightly coupled. The three main components of the architectural framework are cloud client, central server and adhoc network.

CLOUD CLIENT
It's like a master component of the cloud. This client sends request to the central server. SOAP protocol is used as communicating medium among the connected devices. This is the master user as this controls the all the query. It offloads all it works to the central server.

CENTRAL SERVER/Resource Manager
It is the heart of the architecture. It gets all the SOAP requests from the master that is cloud client and converts into XML language. This server uses basic job sharing algorithm for distribute the job & intimidate to the other cloud connected devices according to their resource and capabilities. It acts as a resource manager.

AD-HOC NETWORK/Job Handler
It is the bunch of connected devices which is responsible for the load balance. These are kind of slave devices who acts on getting the SOAP request from the server. Whole devices share the same cloud and every device gets the SOAP request from the central server depending on the size of task from the master cloud client. Once the jobs have been distributed, the clients would proceed to execute their job/s. When the job handler (client) devices finish their job, result are sent back to the master and reassembled.
SOAP receiver: Ad-hoc network

Processof Cloud Request and Response
Mobile user send the request to the cloud server, it passes through many step until acceptance andrun or rejected. This process is shown in figure 4.As can be seen in figure 4, Cloud users(Job submitter) send the request to the cloud sever to distribute or schedule the jobs according their cost and availability time of volunteers(Job processor) and after they send the response to cloud user through cloud servers . This entire step described in following:

Job Scheduling
Proposed Algorithm described as follows: Step 1: Cloud user send job request to the server.
Step2: Job request will be store in the JOB QUEUE according to their occurrence time.
Step 3: Select the ready job from the JOB QUEUE and put into BUFFER the job according.
Step 4: Place this job into VIRTUALE MACHINE and process the job according to the FCFS (First Come First Serve) algorithm method.
Step 5: Scheduler distribute the sorted list according to the mobile client and balance loader and send to the Resource pool.
Step 6: Repeat Step 3 to 5 for next set of job.

Image Processing:-
Image processing is a form of signal processing for which the input is an image, the output of image processing may be either an image or a set of characteristics or parameters related to the image. Image processing is a process to convert an non edited image into more clear image through converting into digital signals in order to get more detailed image or to apply some more effects on it .The purpose of image processing are image sharpening, restoration , visualization ,image recognition etc.

5.4.1Gray Scale
Gray-scale images represent data per element in a shade of gray that ranges in intensity from zero (being black) to a maximum (being white) with various shades [13]. For example, an 8-bit gray scale will range from 0 to 255, providing 256 different possible levels of brightness. [13]

Conversion to Gray Scale
There are many methods to define how to get majority of colour images arestore in image. A common conversion to gray scale is to take an average of the three values. However, a weighted average of these three values is more appropriate to form a the relative brightness for the sum of the three system. [13][14][15][16]

Gray Level Transformation Functions
To define a function that maps a gray level in the in This is called a Gray Level Transformation function, and it looks like this: Where and represent a certain gray level, and it is every pixel on the image. These functions can be used for contrast enhancement, contrast stretching, or thresholding. There is some inverse function that exists that will return th data. [13][14][15][16]

Implementation and Result
In my thesis, I am takingan Image as a job scheduled according to their time and user and Laptop users).Allare connected to the Cloud server by using Wi process the job and convert the image into Gray scale image

Conversion to Gray Scale
There are many methods to define how to get a gray-scale image according to the user format.The arestore in RGB (red, green, blue), and are combined to form the final image. A common conversion to gray scale is to take an average of the three values. However, a weighted average of these three values is more appropriate to form a gray intensity that preserves the relative brightness for the sum of the three colour components according to the human vision Gray Level Transformation Functions define a function that maps a gray level in the input image to a gray level in the output image. This is called a Gray Level Transformation function, and it looks like this: [15] tain gray level, and it is defined between 0 and 1.Eq (2) every pixel on the image. These functions can be used for contrast enhancement, contrast here is some inverse function that exists that will return th

and Result
Image as a job to convert into gray image, which is distribute or scheduled according to their time and cost to number of Job processor (Mobile users, Computer are connected to the Cloud server by using Wi-Fi connection convert the image into Gray scale image by using formula (1).  Eq (2) is applied to every pixel on the image. These functions can be used for contrast enhancement, contrast here is some inverse function that exists that will return the original which is distribute or users, Computer connection. They Step: 1 Job submitter connect via Wi-Fi to cloud server by using IP address of Server.
Step: 2 Job Submitter browse the original picture and submit and upload into server show in figure [7].
Step: 3 When upload image to the server, it start to scheduling or distribute the jobs to Job Processor according their time n cost.
Step: 4 Job Processors connect to cloud server and it will get jobs according their cost and time performance show in figure [8].
Step Step 6: Send the response with grey image to Job submitter.
Step 7: Job Processor get money according the jobs count and cost Job highest Priority sequence will be shown as below:-Cost 1 > Cost 2 > Cost 3 (*coz cost 1take least amount compare to cost 2 and cost 3)

SIMULATION OF INSTRUMENT
In simulation with Cloud Analyst tools, there are two main components which are introduced below.Two phones are Samsung Star Pro S7262,Samsung Galaxy Grand Neo Gti9060and a PC were used in experiments. These three devices were used since they represent a range (low end mobile, high end mobile, resource rich PC) of devices.  Table 2.Server Specification Scenario1:-We had an experiment of our implementation of our software. We used Go daddy specification for testing on cloud computing. We took four kind of server configuration from the vendor • VMware Based: -We configured five VM on it with 1GB RAM and different OS on all the VM for checking the cloud computing traffic. • Cirtrixxen server:-We configured same five OS on xen server also but we found out that xencitrix is easy for mobile traffic also.
Observations: -When we start the job from client as laptop and pc then we were having good job scheduler. We are getting good response time and as well as processing time. We were doing on all the five VM simultaneously for the traffic generations we used standard tool IOMETER_1.1. We generated both kind of random as well as sequential jobs for the server.
Scenario2:-We noticed that we are getting very good performance with PC and laptop clients. Then we thought why not we are merging the code for the mobile also. Right now all the enterprise are using different kind of job scheduler software for the mobile traffic and laptop traffic. So we merged the code to see how the code will perform having laptop and mobile traffic simultaneously. We configured 10 VM (virtual machine) for the test configuration. Thenwe observed that processing time and response were little bit on higher side but when we configured 10 Data Centres then we are getting approximate same values as were getting before.Please find the comparative data for the above test below:- Figure 8 Average processing time Figure 9 Average response of laptop and mobile

CONCLUSION
The concept of cloud computing and job sharing over cloud provides a brand new opportunity for the development of mobile applications that can get heavy tasks done over cloud by offloading computation tasks on cloud, it allows smart mobile devices to retain a small layer for consumer applications and change the processing overhead to the virtual situation. Using the proposed framework the usefulness of job sharing workload at runtime reduces the load at the local client and the dynamic throughput time of the job through Wi-Fi Connectivity instead of the Bluetooth.