A Game-Theoretical Approach for User Allocation in Edge Computing Environment

• Published in: IEEE transactions on parallel and distributed systems Vol. 31; no. 3; pp. 515 - 529
• Main Authors: He, Qiang, Cui, Guangming, Zhang, Xuyun, Chen, Feifei, Deng, Shuiguang, Jin, Hai, Li, Yanhui, Yang, Yun
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Bandwidth; Cloud computing; Computer networks; cost-effectiveness; Distributed processing; Edge computing; edge server; Edge user allocation; Energy conservation; Energy consumption; Game theory; Games; Internet of Things; Mobile computing; multi-tenancy; Nash equilibrium; Network latency; pay-as-you-go; Resource management; Servers; User requirements
• ISSN: 1045-9219; 1558-2183
• DOI: 10.1109/TPDS.2019.2938944

Edge Computing provides mobile and Internet-of-Things (IoT) app vendors with a new distributed computing paradigm which allows an app vendor to deploy its app at hired edge servers distributed near app users at the edge of the cloud. This way, app users can be allocated to hired edge servers nearby to minimize network latency and energy consumption. A cost-effective edge user allocation (EUA) requires maximum app users to be served with minimum overall system cost. Finding a centralized optimal solution to this EUA problem is NP-hard. Thus, we propose EUAGame, a game-theoretic approach that formulates the EUA problem as a potential game. We analyze the game and show that it admits a Nash equilibrium. Then, we design a novel decentralized algorithm for finding a Nash equilibrium in the game as a solution to the EUA problem. The performance of this algorithm is theoretically analyzed and experimentally evaluated. The results show that the EUA problem can be solved effectively and efficiently.