A game theoretic resource allocation for overall energy minimization in mobile cloud computing system

Ge, Yang; Zhang, Yukan; Qiu, Qinru; Lu, Yung-Hsiang

doi:10.1145/2333660.2333724

Cited by 101 publications

(55 citation statements)

References 12 publications

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“…A randomized algorithm [12] determines the optimal solution for QoS-aware task allocation by selecting the appropriate cloud provider for each application execution. Game-theoretic resource allocation framework [13] allocates the resources based on the device energy. It employs the Nash equilibrium algorithm to resolve the energy minimization problem as the congestion game in a mobile cloud environment.…”

Section: Related Workmentioning

confidence: 99%

“…In this case, the BF policy is based on the selection of lowest availability of resources and negligible dominance value of one task on others. It is done by cooperatively selecting the optimal resource for the dominant task or preceding task within the coalition resources using equation (13). It also satisfies the maximum utilization of each resource while hierarchically scheduling the tasks based on the estimated makespan (M).…”

Section: Iot Adaptive Resource Allocation In Mobile Cloudmentioning

confidence: 99%

“…UN(P(ti))cj is the utilization of predecessor on all the coalition resource (cj) excluding the resource providing the dominance result for that specific predecessor. Using equation (13), the GAF-SMART schedules the i th task on the j th cloud resources based on the higher weight of scheduling plan on a particular resource. Thus, the GAF-SMART manipulates the cloud resources while executing the IoT mobile application and provides the energy-efficient cloud services.…”

Section: Iot Adaptive Resource Allocation In Mobile Cloudmentioning

confidence: 99%

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Towards Maximum Resource Utilization and Optimal Task Execution for Gaming IoT Workflow in Mobile Cloud

Shakkeera¹,

Tamilselvan²

2017

IJIES

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Abstract:With the rapid and tremendous growth of real-time resource discovery process ubiquitously, Internet of Things (IoT) and mobile cloud technologies have become an essential part of the future internet. The adaptive and energy-efficient mobile application execution is still in its infancy stage due to the diversity of IoT applications, manipulating workflow of an application and handling a large volume of streaming data in the heterogeneous resource-rich environment. To overcome these constraints, this paper introduces a GAming IoT workflow Fuzzifiers and Supporting MAximum Resource utilization and optimal Task execution on mobile cloud (GAF-SMART) paradigm offering an intelligent way of computing the mobile applications on the remote server. The GAF-SMART employs Game-theory and Fuzzy logic assisted adaptive task scheduler to attain optimal execution for maintaining a workflow of an application. Thus, the proposed mobile cloud IoT paradigm offers high Quality of Service (QoS), increases resource utilization and minimizes the mobile device energy.

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Section: Related Workmentioning

confidence: 99%

Section: Iot Adaptive Resource Allocation In Mobile Cloudmentioning

confidence: 99%

Section: Iot Adaptive Resource Allocation In Mobile Cloudmentioning

confidence: 99%

See 1 more Smart Citation

Towards Maximum Resource Utilization and Optimal Task Execution for Gaming IoT Workflow in Mobile Cloud

Shakkeera¹,

Tamilselvan²

2017

IJIES

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“…In our model the utility is defined as user's energy consumption. Unlike models proposed by Ge et al (2012), Chen (2015) and Chen et al (2015) which do not refer to job deadlines, the job completion times in our model are subject to hard deadline constraints that may vary from user to user. Users intend to minimize their utility function (energy consumption) while not violating their specified job completion time constraints.…”

Section: Motivationmentioning

confidence: 99%

Energy efficient offloading for competing users on a shared communication channel

Meskar

Todd

Zhao

et al. 2015

2015 IEEE International Conference on Communications (ICC)

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In this thesis we consider a set of mobile users that employ cloud-based computation offloading. In computation offloading, user energy consumption can be decreased by uploading and executing jobs on a remote server, rather than processing the jobs locally. In order to execute jobs in the cloud however, the user uploads must occur over a base station channel which is shared by all of the uploading users. Since the job completion times are subject to hard deadline constraints, this restricts the feasible set of jobs that can be remotely processed, and may constrain the users ability to reduce energy usage. The system is modelled as a competitive game in which each user is interested in minimizing its own energy consumption. The game is subject to the real-time constraints imposed by the job execution deadlines, user specific channel bit rates, and the competition over the shared communication channel. The thesis shows that for a variety of parameters, a game where each user independently sets its offloading decisions always has a pure Nash equilibrium, and a Gauss-Seidel method for determining this equilibrium is introduced. Results are presented which illustrate that the system always converges to a Nash equilibrium using the GaussSeidel method. Data is also presented which show the number of Nash equilibria that are found, the number of iterations required, and the quality of the solutions.We find that the solutions perform well compared to a lower bound on total energy

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“…Game theory has been successfully applied to various problems such as congestion control, routing and networking Altman et al (2006); Roughgarden (2010), fairly allocating resource for cloud computing services Ge et al (2012); Niyato et al (2011), detecting intrusion Lo et al (2010), cheating in clouds computing Carroll and Grosu (2011);Hu et al (2012) and cooperating to share files Yang et al (2012) etc. Yang et al studied cooperative communication Yang et al (2012), where nodes in networks make decisions in line with their interests.…”

Section: Related Workmentioning

confidence: 99%

File sharing in cloud computing using win stay lose shift strategy

Wang

Susilo

et al. 2015

IJHPCN

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Traditionally, users in clouds are assumed to be willing to store and share files in clouds, where the security and efficiency issues are discussed. However, few studies involve the incentives to share files in clouds. In this paper, we delve into users' incentives for using the cloud system to store and share their files towards the view of game theory. More specifically, the process of file sharing is reduced to an infinitely repeated prisoner's dilemma PD game and the action of sharing files in clouds is considered as the action of cooperation in the infinitely repeated PD game. We incorporate win stay lose shift WSLS strategy into file sharing and simulate it compared with tit-for-tat TFT strategy in clouds. Simulation results show that WSLS is an optimal strategy for users to share their files in clouds. Furthermore, WSLS is robust for unintentional deviation and returns to mutual cooperation after deviation. Abstract: File sharing in clouds means that users store and share their files in clouds, which can greatly improve the utilization rate of the files. Traditionally, users in clouds are assumed to be willing to store and share their files in clouds, where the security and efficiency issues are discussed. However, little works involve the incentives for users to share files in clouds. That is, why user are willing to share files in clouds. In this paper, we delve into users' incentives for using the cloud system to store and share their files towards the view of game theory. More specifically, the process of file sharing is reduced to an infinitely repeated prisoner's dilemma (PD) game and the action of sharing files in clouds is considered as the action of cooperation in the infinitely repeated PD game. The main task of this paper is to find proper strategies such that users in clouds have incentives to share their files with others. To complete this task, we incorporate Win-Stay-Lose-Shift (WSLS) strategy into file sharing and simulate it compared with Tit-for-Tat (TFT) strategy in clouds. Simulation results show that WSLS is an optimal strategy for users to share their files in clouds. That is, the rounds needed for users to adopt cooperation when they take WSLS are fewer than those when they take TFT. Furthermore, WSLS is robust for unintentional deviation and returns to mutual cooperation after deviation. However, TFT is not robust for unintentional deviation. Thus WSLS is better than TFT for users to share files in clouds.Keywords: File sharing, Win stay lose shift strategy, Game theory, Cloud computing. Qiuliang Xu is a Professor and doctoral supervisor of computer science and technology at Shandong University. Currently he is a sub-decanal of department of science and technology at Shandong University. He has long-term research on theoretical study of information security, cryptology etc. He has published more than 30 high-quality papers in the most famous academic publications in recent five years. Now he is a chair of Nation Science Foundation of China and other foundations.

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A game theoretic resource allocation for overall energy minimization in mobile cloud computing system

Cited by 101 publications

References 12 publications

Towards Maximum Resource Utilization and Optimal Task Execution for Gaming IoT Workflow in Mobile Cloud

Towards Maximum Resource Utilization and Optimal Task Execution for Gaming IoT Workflow in Mobile Cloud

Energy efficient offloading for competing users on a shared communication channel

File sharing in cloud computing using win stay lose shift strategy

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