Energy-saving Strategy for Edge Computing by Collaborative Processing Tasks on Base Stations

Abstract

Mobile Edge Computing (MEC) can significantly save the energy consumption of small-cell base stations(SBSs) by using Dynamic Voltage Scaling (DVS) technology. In this paper, we study how to reduce energy consumption of SBSs by using DVS technology. We propose a scheme to divide base station groups in wireless MEC network, and SBSs in the same base station group collaboratively process tasks. For cooperating tasks in a base station group, we propose a task-offloading strategy, which can effectively reduce the energy consumption of the base station groups. We use Task-offloading Decision Algorithm (TDA) to decide the number of task fragments allocated to each SBSs in the base station group. For processing task fragments in the task queue of SBSs, we propose a computing resource allocation scheme, and we can get the processing time of every task fragments in the task queue by Task Fragments Processing Algorithm (TFPA). Experimental results show that the task-offloading strategy and computing source allocation scheme can reduce the energy consumption by 30%-40% in a cellular network composed of 100 base stations.