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Fast Algorithms for Capacitated Cloudlet Placements

机译:用于电容Cloudlet放置的快速算法

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摘要

Mobile cloud computing addresses resource scarcity problem of mobile devices by offloading computation data from mobile devices into the cloud. However, remote server may be far from mobile users. Cloudlet could be used to deal with the long access delay problem. In the large-scale Wireless Metropolitan Area Network (WMAN) consisting of many wireless Access Points (APs), choosing the appropriate position of cloudlet is very important to reducing access delay. Recently, a heuristic algorithm has been proposed. However, it has so many repeated sorting process of APs that the algorithm efficiency is poor. In this paper, we propose a New Heuristic Algorithm (NHA) and a Particle Swarm Optimization (PSO) algorithm for the delaying problem. We evaluate the performance of the proposed algorithms through extensive simulations. Simulation results demonstrate NHA is more efficient then existing algorithm. For the PSO algorithm, in the case of parallelized execution, it is more efficient than the new heuristic algorithm within a bounded delay.
机译:移动云计算通过将来自移动设备的计算数据从移动设备卸载到云中来解决移动设备的资源稀缺问题。但是,远程服务器可能远离移动用户。 Cloudlet可用于处理长途访问延迟问题。在由许多无线接入点(APS)组成的大型无线大都市区域网络(WAN)中,选择Cloudlet的适当位置对于降低访问延迟非常重要。最近,已经提出了一种启发式算法。但是,它有很多重复排序过程的APS算法效率差。在本文中,我们提出了一种新的启发式算法(NHA)和用于延迟问题的粒子群优化(PSO)算法。我们通过广泛的模拟评估所提出的算法的性能。仿真结果证明了NHA更有效,然后是现有的算法。对于PSO算法,在并行执行的情况下,它比在界限延迟内的新启发式算法更有效。

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