期刊
IEEE TRANSACTIONS ON CLOUD COMPUTING
卷 9, 期 1, 页码 1-13出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCC.2018.2790404
关键词
Distributed environment; load balancing; non-cooperative game; nash equilibrium; server availability; variational inequality theory
类别
资金
- National Key R&D Program of China [2016YFB0201402]
- National Natural Science Foundation of China [61702170, 61602350, 61602170, 61402400, 61370098, 61672219]
- Key Program of National Natural Science Foundation of China [61432005]
- National Outstanding Youth Science Program of National Natural Science Foundation of China [61625202]
- National High-tech R&D Program of China [2015AA015305]
- Chinese Postdoctoral Science Foundation [2016M602409, 2016M602410]
This paper focuses on request migration strategies among multi-servers for load balancing in a distributed, non-cooperative, and competitive environment. By formulating the problem as a non-cooperative game among servers and utilizing variational inequality theory, the authors propose an iterative proximal algorithm that converges to a Nash equilibrium solution which significantly decreases the disutilities of all servers.
In this paper, we focus on request migration strategies among multi-servers for load balancing. Different from the general load balancing problem, we consider it under a distributed, non-cooperative, and competitive environment. Due to the mentioned characteristics, we view our problem from a game theoretic perspective and formulate it into a non-cooperative game among the multiple servers, in which each server is informed with incomplete information of other servers. For each server, we define its expected response time as a disutility function and try to minimize its value. We also take into account server availability, which impacts the processing capacity of a server and thus its disutility. We solve the problem by employing variational inequality (VI) theory and prove that there exists a Nash equilibrium solution set for the formulated game. Then, we propose an iterative proximal algorithm (IPA) to compute a Nash equilibrium solution. The convergence of the IPA algorithm is also analyzed and we find that it converges to a Nash equilibrium. Finally, we conduct some numerical calculations to verify our theoretical analyses. The experimental results show that our proposed IPA algorithm converges to a Nash equilibrium very quickly and significantly decreases the disutilities of all servers by configuring a proper request migration strategy.
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