Focused on the high latency and energy consumption for computational offload in mobile edge computing scenarios with device-to-device(D2D)communication technology,a computational offloading strategy based on multi-objective optimiza-tion is proposed.The strategy is based on a computing offloading model with multi-objective optimization of delay and energy con-sumption,introduces the analysis of excessive offloading problem,improves the NSGA-Ⅱ algorithm,including genetic encoding strategy,crossover and variation methods applicable to computing offloading,and minimizes task execution time and energy con-sumption by solving the Pareto optimum.In addition,a data routing algorithm is proposed,which balances the transmission en-ergy consumption of routing devices and optimizes the routing paths.Through simulation experiments,the average boosting effi-ciency of the algorithm is up to 41.7%and the task retransmission rate is reduced to 7.8%.The experiment results show that the proposed algorithm can significantly reduce the execution delay,energy consumption,task retransmission rate and improve the task offload success rate.
维普
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