Energy-Aware and Deadline-Constrained Task Allocation in Game-Based Mobile Cloud
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Published:2022-01-22
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Volume:
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ISSN:0218-0014
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Container-title:International Journal of Pattern Recognition and Artificial Intelligence
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language:en
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Short-container-title:Int. J. Patt. Recogn. Artif. Intell.
Author:
Yang Zhuoxi1,
Ding Yan2,
Zhao Jia2ORCID
Affiliation:
1. College of Software, Beihang University, Beijing, P. R. China
2. Artificial Intelligence Institute of Technology & School of Computer Technology and Engineering, Changchun Institute of Technology Changchun, P. R. China
Abstract
A mobile community can be composed of multiple mobile devices through D2D (Device-to-Device) network. In many cases, these mobile devices cannot conveniently connect to the Internet, for various reasons. To overcome this obstacle, one solution is to let the mobile devices cooperate with each other through a D2D-enabled network, forming a mobile community that, as a whole, may be able to autonomously execute the tasks requested by its members. To maximize the overall benefits of mobile communities, this paper proposes a novel task allocation approach, EDTG (Energy-aware and Deadline-constrained Task allocation using Game theory). In mobile communities, energy consumption is responsible for the largest part of the cost. Energy management can lead to performance degradation and even be perceived as a bottleneck, while load balancing between devices can improve service performance and resource utilization to the largest extent. EDTG has considered both the inevitable performance constraints at each device and a method based on the connectivity of graph theory, in order to narrow down the search scope of optimal target mobile devices where requested tasks can be executed. The “Bargaining Game” method is designed and exploited to obtain the final task allocation solution. Final experimental results demonstrate that compared to existing approaches, EDTG ensures high-performance task execution and reaches the goal of maximizing the overall benefits to some extent, by achieving better energy savings and exploiting load balancing between devices.
Funder
National Natural Science Foundation of China
The 13th Five-Year Plan Key Science and Technology Research Projects of Jilin Provincial Education Office
The Theme Fund of Changchun Institute of Technology
The Key R & D Project of Jilin Province Science and Technology Development Plan
The Industrial Technology R & D Special Project of Jilin Provincial Development and Reform Commission
The Fourth Batch of Jilin Province Youth S & T Talent Lift Project
The Scientific Research Initiation Fund for Doctoral Innovation Team
Publisher
World Scientific Pub Co Pte Ltd
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software