Distributed Hybrid Task Offloading in Mobile-Edge Computing: A Potential Game Scheme

Mobile-edge computing introduces a novel computing paradigm for mobile devices (MDs), reducing execution latency and energy consumption by offloading tasks to edge servers or other idle MDs. In this article, we consider the utility optimization problem of two typical computing tasks, latency-sensitive tasks and latency-tolerant tasks, among multiple MDs and base stations (BSs). MDs can choose three computing modes to optimize utility: 1) local computing; 2) task allocation to BSs; and 3) task allocation to other MDs through device-to-device communication. To address this problem, we formalize it as a potential game for multi-MD multi-BS task offloading. Furthermore, we prove the existence of a Nash equilibrium for the modeled potential game and propose a task allocation scheme for hybrid tasks. This scheme maximizes both energy consumption utility and task execution utility by optimizing task offloading mode selection and task execution order scheduling. Simulation results show that our proposed scheme can substantially enhance user utility and has good scalability with the increase of MDs.