针对终端直传(Device-to-Device,D2D)通信技术的移动边缘计算场景中计算卸载的高时延、高能耗问题,提出一种基于多目标优化的计算卸载策略.该计算卸载策略基于时延和能耗多目标优化模型,引入过度卸载问题的分析,对NSGA-Ⅱ算法进行改进,包括适用于计算卸载的基因编码策略、交叉和变异方法,通过求解帕累托最优来最小化任务执行时间和能耗.此外,还提出一种数据路由算法,以平衡路由设备的传输能耗,并优化路由路径.通过仿真实验,该算法的平均提升效率最高可达41.7%,任务重传率降低至7.8%.实验结果表明,本文提出的算法能明显减少执行时延、能耗,降低任务重传率和提高任务卸载成功率.
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.