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Server deployment planning and performance analysis in mobile edge computing with β-Ginibre point process

机译:使用β-Ginibre点过程的移动边缘计算中的服务器部署规划和性能分析

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Mobile Edge Computing (MEC) has been included in the architecture of 5G network, which is expected to give users access to approximate edge servers and reduce latency of computation-intensive applications. The deployment of MEC servers is significantly different with that of wireless cellular network base stations, since it needs to take transmission quality, coverage of the station/server and computational resource provisioning into account comprehensively. β-Ginibre point process comes from a recently studied stochastic geometry theory, which enables simulation of base station locations that could approximate better real station distribution. In this paper, an application of β-Ginibre point process in the deployment and location choice of MEC servers is presented, we then analyze the coverage and latency performance based on β-Ginibre point process. Extensive simulations verify that the proposed server deployment planning could increase coverage on mobile users and reduce the latency of MEC services.
机译:移动边缘计算(MEC)已包含在5G网络的体系结构中,有望使用户能够访问近似的边缘服务器并减少计算密集型应用程序的延迟。 MEC服务器的部署与无线蜂窝网络基站的部署显着不同,因为它需要综合考虑传输质量,站点/服务器的覆盖范围和计算资源的提供。 β-Ginibre点过程来自最近研究的随机几何理论,该理论使得能够模拟可以更好地逼近实际基站分布的基站位置。本文介绍了β-Ginibre点过程在MEC服务器的部署和位置选择中的应用,然后基于β-Ginibre点过程分析了覆盖范围和时延性能。大量的仿真证明,建议的服务器部署计划可以增加移动用户的覆盖范围并减少MEC服务的延迟。

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