计算机科学 ›› 2022, Vol. 49 ›› Issue (6): 12-18.doi: 10.11896/jsjkx.211200147
周天清, 岳亚莉
ZHOU Tian-qing, YUE Ya-li
摘要： 随着物联网(Internet of Things,IoT)的迅速发展,各种物联网移动设备(IoT Mobile Device,IMD)需要处理越来越多的计算密集型和延迟敏感型任务,这给移动边缘计算网络带来了新的挑战。为了应对这些挑战,装备移动边缘计算(Mobile Edge Computing,MEC)的超密集物联网应运而生。在该网络中,IMD可将计算密集型任务卸载至边缘计算服务器上进行处理,从而节省自己的计算资源并降低能耗。然而,这样会造成额外的传输时间,进而导致更高的延迟。为了均衡能耗与时延,针对多用户多任务的超密集物联网络,提出了一个最小化能耗和时延的均衡问题,以联合优化用户(IMD)关联、计算卸载和资源分配。为了进一步平衡网络负载,充分利用计算资源,在问题建模时采用多步计算卸载。最后,利用智能算法——自适应粒子群算法(Particle Swarm Optimization,PSO) 对所提问题进行求解。相比传统粒子群算法,自适应粒子群算法能降低20%~65%的总开销。
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