Joint Optimization Task Offloading Strategy for Mobile Edge Computing

With increase of Internet of Things (IoT) devices, the burden of cloud computing servers is gradually increasing. Mobile Edge Computing (MEC), as an emerging solution, can relieve the pressure of computing and improve the quality of user experience. One of the critical challenges in MEC is to make effective use of communication and computing resources and select the task processing mode reasonably. In this paper, based on the scenario of a single mobile device (MD) to one mobile edge server (MES), we propose a Joint optimization method base on Discrete Binary Particle Swarm Optimization Algorithm (JOBPSO) for system load. The JOBPSO can optimize MD's task offloading, reduce delay and energy consumption. Finally, the simulation results indicate that the performance of JOBPSO in reducing system load is better than the other two traditional offloading methods.

I. Introduction

In the last few decades, the number of mobile devices (MDs) has increased dramatically. It is difficult for cloud computing servers to handle the tasks generated by mobile devices. Since cloud servers usually are deployed at the core of the Internet, and users' traffic has to travel a long distance to get served, and therefore, end users may experience a long response time [1].