Joint Channel Allocation and Resource Management for Stochastic Computation Offloading in MEC

Abstract

To accommodate ever-increasing computational workloads while satisfying the requirements of delay-sensitive tasks, mobile edge computing (MEC) is proposed to offload the tasks to nearby edge servers. Nevertheless, it can introduce new technical issues in terms of transmission and computation overheads affected by the underlying offloading decisions. In this paper, we investigate the computation offloading problem in a hierarchical network architecture, where tasks can be offloaded to nearby micro-BS and further forwarded to macro-BS equipped with an MEC server. Specifically, we propose a scheme of joint channel allocation and resource management, named JCRM, to make offloading decisions and maximize the long-term network utility with considering stochastic task arrival/dispatch and dynamic changes in available resources. As the formulated utility maximization problem is a mixed-integer non-linear stochastic programming problem that is directly intractable, we, therefore, leverage the Lyapunov optimization technique to decouple the original problem into three separate sub-problems. Based on the solutions to those sub-problems, our proposed scheme can make optimal offloading-downloading decisions with maximizing the overall task offloading rate. Finally, we verify the long-term network stability and near-optimal performance of JCRM via both theoretical analysis and extensive simulations.