A Bilevel Optimization Approach for Joint Offloading Decision and Resource Allocation in Cooperative Mobile Edge Computing

Peiqiu Huang, Yong Wang*, Kezhi Wang*, Zhi-Zhong Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

96 Citations (Scopus)
75 Downloads (Pure)

Abstract

This paper studies a multi-user cooperative mobile edge computing offloading (CoMECO) system in a multi-user interference environment, in which delay-sensitive tasks may be executed on local devices, cooperative devices, or the primary MEC server. In this system, we jointly optimize the offloading decision and computation resource allocation for minimizing the total energy consumption of all mobile users under the delay constraint. If this problem is solved directly, the offloading decision and computation resource allocation are generally generated separately at the same time. Note, however, that they are closely coupled. Therefore, under this condition, their dependency is not well considered, thus leading to poor performance. We transform this problem into a bilevel optimization problem, in which the offloading decision is generated in the upper level, and then the optimal allocation of computation resources is obtained in the lower level based on the given offloading decision. In this way, the dependency between the offloading decision and computation resource allocation can be fully taken into account. Subsequently, a bilevel optimization approach, called BiJOR, is proposed. In BiJOR, candidate modes are first pruned to reduce the number of infeasible offloading decisions. Afterward, the upper level optimization problem is solved by ant colony system (ACS). Furthermore, a sorting strategy is incorporated into ACS to construct feasible offloading decisions with a higher probability and a local search operator is designed in ACS to accelerate the convergence. For the lower level optimization problem, it is solved by the monotonic optimization method. In addition, BiJOR is extended to deal with a complex scenario with the channel selection. Extensive experiments are carried out to investigate the performance of BiJOR on two sets of instances with up to 400 mobile users. The experimental results demonstrate the effectiveness of BiJOR and the superiority of the CoMECO system.
Original languageEnglish
Pages (from-to)4228-4241
Number of pages14
JournalIEEE Transactions on Cybernetics
Volume50
Issue number10
Early online date19 Jun 2019
DOIs
Publication statusPublished - Oct 2020

Keywords

  • Ant colony system (ACS)
  • bilevel optimization
  • computation resource allocation
  • mobile edge computing (MEC)
  • offloading decision

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