Location-Aware Task Offloading for MEC-based High Mobility Service

Multi-access Edge Computing (MEC) is a paradigm which moves the capabilities of Central Cloud closer to the edge of the network. In this paradigm, several Edge Clouds are deployed at the network edge to perform tasks from end-users and guaranteeing low network delay to the users. This paper focuses on MEC services, where tasks from users are offloaded to either Edge Cloud or Central Cloud. The task offloading problem intends to select the most proper cloud to perform a task. Such selection problem is complex, especially when the mobility of users is involved. We proposed a Location-Aware Task Offloading policy to reduce the service time, which is the combination of processing time and network delay. Performance evaluation shows that the proposed policy outperforms existing baseline policies up to 15% better than the resource-based policy, and performs 22% better than latency-based policy in terms of service time.