In mobile edge computing(MEC)networks,to solve the problem of computation offloading for multiple computing-intensive tasks on multiple local devices,a computation offloading strategy based on improved particle swarm optimization(PSO)was proposed to obtain the optimal offloading decision and resource allocation scheme.First,aiming at minimizing the computational offload cost related to the delay and the energy consumption,considering the task balance between MEC servers,a computation offloading system model in a multi-user,multi-task,and multi-server scenario was built.The weights of the delay and the energy consumption were adjusted adaptively according to the residual energy and charging state of the devices.Then,to minimize the corrected weight sum of the delay and energy consumption,an improved PSO algorithm was proposed to obtain the optimal task offload decision and computing resource allocation scheme.The simulation results showed that,the proposed scheme could reduce the system cost by 20%compared with the offloading scheme based on genetic algorithm.
维普
万方数据