Task Offloading Scheduling in Mobile Edge Computing Networks

In this paper, we investigate the task scheduling in resource-limited mobile edge computing (MEC) network, where multiple base stations (BSs), each equipped with a MEC server, assist multiple latency-sensitive user equipments (UEs) in computing. We aim to jointly minimize the system energy consumption and maximize the number of offloaded tasks by optimizing the task scheduling between UEs and BSs. A multiple-objective and mix-integer problem is formulated, which is difficult to solve. To tackle the problem, we combine the ant colony optimization (ACO) algorithm with load balancing, and propose an efficient algorithm. The simulation demonstrates the effectiveness of the proposed algorithm. (C) 2021 The Authors. Published by Elsevier B.V.