计算机科学 ›› 2021, Vol. 48 ›› Issue (11A): 456-463.doi: 10.11896/jsjkx.210100191
姚泽玮, 林嘉雯, 胡俊钦, 陈星
YAO Ze-wei, LIU Jia-wen, HU Jun-qin, CHEN Xing
摘要： 移动边缘计算(Mobile Edge Computing,MEC)作为一种新的范式,可以解决移动设备的计算资源、存储资源短缺的问题。通过无线网络,它将移动设备上的密集型任务迁移到用户附近的边缘上执行,最后把运行结果传回给移动设备。由于用户移动的随机性,部署在城市的每个边缘的负载情况通常是不一致的。针对多边缘的负载均衡问题,考虑通过任务调度来最小化边缘集合中最大的任务响应时间,从而提高移动设备的性能。首先,对多边缘负载均衡问题进行形式化定义;其次,提出粒子群遗传算法(Particle Swarm Optimization-Genetic Algorithm,PSO-GA)来解决多边缘负载均衡问题;最后通过仿真实验,将该算法与随机迁移算法和贪心算法进行对比与分析。实验结果表明,PSO-GA得到的结果最高分别优于随机迁移算法和贪心算法51.58%和26.34%。因此,PSO-GA在缩短边缘的任务响应时间、改善用户体验方面具有较好的潜力。
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