Quality of experience-aware user allocation in edge computing systems: a potential game

Phu Lai, Qiang He, Guangming Cui, Feifei Chen, Mohamed Abdelrazek, John Grundy, John Hosking, Yun Yang

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

8 Citations (Scopus)


As many applications and services are moving towards a more human-centered design, app vendors are taking the quality of experience (QoE) increasingly seriously. End-to-end latency is a key factor that determines the QoE experienced by users, especially for latency-sensitive applications such as online gaming, health care, critical warning systems and so on. Recently, edge computing has emerged as a promising solution to the high latency problem. In an edge computing environment, edge servers are deployed at cellular base stations, offering processing power and low network latency to users within their geographic proximity. In this paper, we tackle the user allocation problem in edge computing from an app vendor’s perspective, where the vendor needs to decide which edge servers to serve which users in a specific area. Also, the vendor must consider the various levels of quality of service (QoS) for its users. Each QoS level results in a different QoE level; thus, the app vendor needs to decide the QoS level for each user so that the overall user experience is maximized. To tackle the NP-hardness of this problem, we formulate it as a potential game then propose QoEGame, an effective and efficient game-theoretic approach that admits a Nash equilibrium as a solution to the user allocation problem. Being a distributed algorithm, QoEGame is able to fully utilize the distributed nature of edge computing. Finally, we theoretically and empirically evaluate the performance of QoEGame, which is illustrated to be significantly better than the state of the art and other baseline approaches.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE 40th International Conference on Distributed Computing Systems, ICDCS 2020
EditorsBingsheng He, Xueyan Tang
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages11
ISBN (Electronic)9781728170022
ISBN (Print)9781728170039
Publication statusPublished - 2020
EventInternational Conference on Distributed Computing Systems 2020 - Virtual, Singapore, Singapore
Duration: 29 Nov 20201 Dec 2020
Conference number: 40th
https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/conhome/9355572/proceeding (Proceedings)
https://icdcs2020.sg (Website)

Publication series

NameProceedings - International Conference on Distributed Computing Systems
PublisherThe Institute of Electrical and Electronics Engineers, Inc.
ISSN (Print)1063-6927
ISSN (Electronic)2575-8411


ConferenceInternational Conference on Distributed Computing Systems 2020
Abbreviated titleICDCS 2020
Internet address


  • Edge computing
  • Game theory
  • Quality of Experience
  • Quality of Service
  • User allocation

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