一种基于遗传算法的多边缘协同计算卸载方案

边缘计算(Edge Computing,EC)作为云计算的补充,在处理lOT设备产生的计算任务时可以保证计算的延时符合系统的要求.针对在传统卸载场景中,由于计算任务到达存在空窗期导致异地边缘云存在空闲状态,造成异地边缘云利用不充分的问题,文中提出了一种基于遗传算法的多边缘与云端协同计算卸载模型(Genetic Algo...

Multi-edge Collaborative Computing Unloading Scheme Based on Genetic Algorithm

As a supplement to cloud computing,edge computing can ensure that the calculation delay meets system requirements when processing computing tasks generated by lOT equipment.Aiming at the problem of insufficient utilization of the remote edge cloud due to the empty window period of the computing task in the traditional offloading scenario,a genetic algorithm-based multi-edge and cloud collaborative computing offloading model(Genetic Algorithm-based Multi-edge Collaborative Computing Offloading Model,GAMCCOM)is proposed.This computing offloading solution combines local edge and remote edge to perform task offloading and uses a genetic algorithm to get the minimum system cost under consideration of both delay and energy consumption at the same time.The results of simulation experiments show that when considering the time delay consumption and energy consumption of the unloading system,the overall cost of this scheme is reduced by 23%compared with the basic three-layer unloading scheme.In the case of considering time delay consumption and energy consumption respectively,the system cost can still be reduced by 17%and 15%respectively.Therefore,the GAMCCOM offloading method can effectively reduce the system cost for different offloading targets of edge computing.