Seamless Service Migration across Multi-access Edge Computing (MEC) Environments

Abstract

Multi-access Edge Computing (MEC) has emerged as a paradigm for enabling cloud computing capabilities at the edge of a mobile network in recent years. For example, mobile edge servers connected to cellular base stations significantly help in the reduction of network overhead and latency across edge clouds. The problem is, however, that mobile users frequently change their geographical location which makes identifying an optimal service migration strategy exceedingly difficult. Hence, the process of service migration across cellular edge environments continues to be a major challenge. As a result, significant network performance degradation, such as service interruptions and increased latency when executing services, is likely to occur. The purpose of this research is to examine the use of a Multiple-Criteria Decision Analysis (MCDA) technique called TOPSIS for optimizing service migration across the edge network. We employ TOPSIS to determine when it is appropriate to migrate the service, as well as suitable resources for the service to migrate to. Additionally, we develop a simulation tool for analyzing the performance of our proposed Service Migration Optimization Model (SOM) through the use of various edge-based user-defined scenarios.