Delay-sensitive Task offloading combined with Bandwidth Allocation in Multi-access Edge Computing

Abstract

In recent years, multi-access edge computing (MEC) has become a hot topic. In this paper, we study a task offloading problem combined with bandwidth allocation in multi-access edge computing. Based on alliance game, we formulate bandwidth allocation to minimize the dissatisfaction of alliances. Then, we formulate the task offloading decision-making to minimize the delay. The delay consists of communication delay and execution delay. To solve the offloading problem, we convert the dissatisfaction of alliance into a vector, and obtain the Pareto optimal through multi-objective particle swarm algorithm. Then, we use Branch and Bound method to construct the propagation tree to facilitate decision-making. To evaluate the edge servers in the tree, we build an evaluation matrix and transform the matrix to a set of evaluation index which is used on task offloading decision-making. A large number of experimental results show that our algorithm is better than compared algorithm.