Dynamic Computation Offloading for Mobile Cloud Computing: A Stochastic Game-Theoretic Approach

被引:258
作者
Zheng, Jianchao [1 ,2 ]
Cai, Yueming [2 ]
Wu, Yuan [3 ]
Shen, Xuemin [4 ]
机构
[1] Acad Mil Sci PLA, Natl Innovat Inst Def Technol, Beijing 100010, Peoples R China
[2] PLA Army Engn Univ, Coll Commun Engn, Nanjing 210007, Jiangsu, Peoples R China
[3] Zhejiang Univ Technol, Coll Informat Engn, Hangzhou 310023, Zhejiang, Peoples R China
[4] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON N2L 3G1, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Mobile cloud computing; multi-user computation offloading; dynamic environment; stochastic game; multi agent stochastic learning; SMALL-CELL NETWORKS; ALLOCATION; RESOURCE;
D O I
10.1109/TMC.2018.2847337
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Driven by the growing popularity of mobile applications, mobile cloud computing has been envisioned as a promising approach to enhance computation capability of mobile devices and reduce the energy consumptions. In this paper, we investigate the problem of multi-user computation offloading for mobile cloud computing under dynamic environment, wherein mobile users become active or inactive dynamically, and the wireless channels for mobile users to offload computation vary randomly. As mobile users are self-interested and selfish in offloading computation tasks to the mobile cloud, we formulate the mobile user's offloading decision process under dynamic environment as a stochastic game. We prove that the formulated stochastic game is equivalent to a weighted potential game which has at least one Nash Equilibrium (NE). We quantify the efficiency of the NE, and further propose a multi-agent stochastic learning algorithm to reach the NE with a guaranteed convergence rate (which is also analytically derived). Finally, we conduct simulations to validate the effectiveness of the proposed algorithm and evaluate its performance under dynamic environment.
引用
收藏
页码:771 / 786
页数:16
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