计算机应用与软件2025，Vol.42Issue(5)：291-297,7.DOI:10.3969/j.issn.1000-386x.2025.05.039
基于粒子群算法的边缘计算任务迁移策略
MIGRATION STRATEGY OF EDGE COMPUTING TASKS BASED ON PARTICLE SWARM OPTIMIZATION
摘要
Abstract
Edge computing is to migrate terminal tasks to the edge server for execution,and reduce task execution delay and terminal energy consumption through reasonable migration decision.In view of the fact that a large number of literatures only consider the unloading decision of multi-task single server and ignore the balance of computing tasks between servers,a multi-task multi-server joint optimization strategy based on particle swarm optimization(PSO)is proposed.Taking the delay and energy consumption as the optimization objectives,considering the queuing delay and the balance of the amount of computation of the edge computing server(MEC),the global computing resources were fully utilized,which further reduced energy consumption and time delay.Simulation results show that,compared with other algorithms,the average task cost of the proposed algorithm is the smallest,which proves the feasibility and high efficiency of the method.关键词
边缘计算/粒子群/排队时延/负载均衡/平均任务成本Key words
Edge computing/Particle swarm optimization/Queuing delay/Load balancing/Average task cost分类
信息技术与安全科学引用本文复制引用
马伟,杨军,马自强..基于粒子群算法的边缘计算任务迁移策略[J].计算机应用与软件,2025,42(5):291-297,7.基金项目
宁夏自然科学基金项目(2020AAC03036) （2020AAC03036）
宁夏回族自治区重点研发计划项目(2021BEG02007). （2021BEG02007）
