Service Migration for Multi-Cell Mobile Edge Computing

Abstract

Mobile-edge computing (MEC) enhances the capacities and features of mobile devices via offloading computation-intensive tasks over wireless networks to the edge servers. One challenge faced by the deployment of MEC in cellular networks is to support user mobility, so that the offloaded tasks can be seamlessly migrated between base stations (BSs) without compromising the resource-utilization efficiency and link reliability. In this paper, we tackle the challenge by optimizing the policy for migration/handover between BSs by jointly managing computation-and-radio resources. The policy design is formulated as a multi-objective optimization problem that maximizes the sum offloading rate, quantifying MEC throughput, and minimizes the migration cost, where the issues of virtualization, I/O interference between virtual machines (VMs), and wireless multi-access are taken into account. To solve the complex combinatorial problem, we develop an efficient relaxation-and-rounding based approach, including an optimal iterative algorithm for solving the integer-relaxed problem and a novel integer-recovery design that exploits the derived problem properties. The simulation results show the close-to-optimal performance of the proposed migration policies under various settings, validating their efficiency in computation-and-radio resource management for joint service migration and BS handover in multi-cell MEC networks.