Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (11A): 230200095-8.doi: 10.11896/jsjkx.230200095

• Network & Communication • Previous Articles     Next Articles

Fairness-aware Service Caching and Task Offloading with Cooperative Mobile Edge Computing

WU Chun, CHEN Long, SUN Yifei, WU Jigang   

  1. School of Computer Science and Technology,Guangdong University of Technology,Guangzhou 510006,China
  • Published:2023-11-09
  • About author:WU Chun,born in 1998,postgraduate.His main research interest is edge computing.
    WU Jigang,born in 1963,Ph.D,professor,Ph.D supervisor,is a member of China Computer Federation.His main research interests include intelligent computing,and mobile computing.
  • Supported by:
    National Natural Science Foundation of China(62072118,62202108) and Natural Science Foundation of Guangdong Province,China(2023A1515011230).

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Abstract: Caching services in edge servers can reduce the response time of user requests and improve user experience.Most of existing works focus on optimizing the overall system performance,i.e.,maximizing the system throughput,which cannot gua-rantee the user fairness in requesting heterogeneous services.To fill this gap,this paper investigates fairness-aware joint service caching and task offloading strategy with cooperative edge computing.A minimum service completion rate maximization problem is formulated based on max-min fairness principle,which is proved to be NP-hard.A randomized rounding algorithm with MS/N(S－2 ln S)-approximation ratio is proposed by transforming the original problem from 0-1 integer programming into linear programming using linear relaxation,where S,N and M are the numbers of edge servers,services and end devices,respectively.Moreover,a fast and efficient greedy algorithm is proposed by caching the service with the minimum completion rate and offloa-ding its corresponding tasks preferentially.Extensive simulation results demonstrate that not only the minimum service completion rate can be improved by at least 44.1% and 90.6% by our two algorithms,but also the extra loss of system throughput is no more than 22.4% and 27.0%,respectively,compared with the existing algorithms for maximizing system throughput.

Key words: Edge computing, Service caching, Task offloading, Max-Min fairness, Randomized rounding

CLC Number: 

  • TP391
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