A game-theoretical approach for user allocation in edge computing environment

Qiang He, Guangming Cui, Xuyun Zhang, Feifei Chen, Shuiguang Deng, Hai Jin, Yanhui Li*, Yun Yang

*Corresponding author for this work

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number8823046
Pages (from-to)515-529
Number of pages15
JournalIEEE Transactions on Parallel and Distributed Systems
Volume31
Issue number3
DOIs
Publication statusPublished - Mar 2020
Externally publishedYes

Keywords

  • cost-effectiveness
  • edge computing
  • edge server
  • Edge user allocation
  • game theory
  • multi-tenancy
  • Nash equilibrium
  • pay-as-you-go

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