Offloading Decision and Resource Allocation Strategy in Mobile Edge Computing

Abstract

In order to minimize the total system cost when the computing resources of Mobile Edge Computing(MEC) servers are limited,this paper designs a multi-user offloading decision and resource allocation strategy.The strategy jointly optimizes the selection of task execution location and the allocation of computing resources,and improves the encoding,crossover and mutation parts of the Genetic Algorithm(GA) based on the elite selection strategy(e-GA).On this basis,improve-eGA algorithm is designed combining offloading decision and resource allocation.Experimental results show that,compared with the ALL_Local algorithm,ALL_Offload algorithm,RANDOM algorithm and Conventional Genetic Algorithm(CGA),etc.,improve-eGA has the smallest total system cost under the influence of the iteration number,CPU working frequency,transferred data size of tasks,etc.,which verifies the validity of the proposed strategy.