Latency-Aware Task Peer Offloading on Overloaded Server in Multi-Access Edge Computing System Interconnected by Metro Optical Networks

Abstract

The Multi-access Edge Computing (MEC) system interconnected by metro optical network is gaining much attention recently. The proximity of computing resources in MEC provides the possibility of low-latency access for user equipment (UE). However, since the computing capacity of edge server is limited, the task failure may occur due to the unacceptable computing latency if the corresponding server is overloaded. Note that there is more than one MEC server at the network edge and the computationally intensive tasks on the overloaded server can be sent to nearby light-loaded servers for processing via peer offloading. In this article, we design a latency-aware task peer offloading (LA-TPO) scheme, which is an economic solution for the overload problem of MEC. We formulate the LA-TPO into a mixed integer non-linear programming (MINLP) model and develop a GA-based heuristic algorithm to jointly optimize the offloading decisions and the routing and computing resource allocation. We compare the MINLP and proposed algorithm under various scenarios, and the results show that the GA-based LA-TPO can achieve low latency, high success ratio of tasks as well as the optimization of resource utilization.