Edge Computing Sever Selection in Fog Radio Access Networks

Xile Shen, Xiaoshi Song, Xiangbo Meng, Chao Jia
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引用次数: 1

Abstract

In this paper, we consider a fog radio access (F-RAN) network formed by two different kinds of node, namely the user and calculator (i.e., the edge computing sever), respectively. It is assumed that the users and calculators follows two independent homogeneous Poisson point processes (HPPPs). Further, it is assumed that the arrival of the computing tasks at each user and the departure of the computing tasks at each calculator follow two Poisson processes with rate ηu and ηc, respectively. That is, the time between successive arrivals at each user or departures at each calculator are independent exponential random variables with mean given by $\frac{1}{{{\eta _u}}}$ or $\frac{1}{{{\eta _c}}}$. Time is divided into slots. At the beginning each time slot, each user is designed to offload the computing tasks generated in the last time slot to their nearby calculators within a distance of Rd for data processing. Different from the random-chosen based calculator selection schemes studied in the previous works, in this paper, we consider a prediction based calculator selection strategy to enhance the delay performance of the F-RAN. Particularly, under the proposed prediction based calculator selection strategy, we estimate the network status in the next time slot, and use which as the criterion for computing server selection and tasks offloading. It is shown through both the analysis and simulations that the proposed prediction based calculator selection strategy outperforms the random-chosen based calculator selection protocol in terms of the successful offloading probability.
雾无线接入网中的边缘计算服务器选择
在本文中,我们考虑由用户和计算器(即边缘计算服务器)两种不同类型的节点组成的雾无线接入(F-RAN)网络。假设用户和计算器遵循两个独立的齐次泊松点过程(hppp)。进一步,假设计算任务到达每个用户处和计算任务离开每个计算器处分别遵循速率为ηu和ηc的两个泊松过程。也就是说,连续到达每个用户或离开每个计算器的时间间隔是独立的指数随机变量,其平均值由$\frac{1}{{{\eta _u}}}$或$\frac{1}{{{\eta _c}}}$给出。时间被划分成不同的时间段。在每个时隙开始时,每个用户将最后一个时隙生成的计算任务卸载到距离Rd的附近计算器上进行数据处理。与以往研究的基于随机选择的计算器选择方案不同,本文考虑了一种基于预测的计算器选择策略来提高F-RAN的延迟性能。特别是,在基于预测的计算器选择策略下,我们估计了下一个时隙的网络状态,并将其作为计算服务器选择和任务卸载的标准。通过分析和仿真表明,基于预测的计算器选择策略在成功卸载概率方面优于基于随机选择的计算器选择协议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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