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Content Caching Policy with Edge Caching User Classification in Fog Radio Access Networks

机译:雾无线电接入网络中边缘缓存用户分类的内容缓存策略

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With the rapid growth of mobile devices and applications, fog radio access network (F-RAN) has been proposed as a promising paradigm for the 5th generation of mobile networks. Meanwhile, F-RAN can be further enhanced by edge caching underpinned by device-to-device (D2D) communications, where the download delay can be reduced by edge caching users (EUs) providing content though D2D links to content requesting users (RUs). In this paper, to mitigate the impact of limited storage at each EU, we propose an EU classification based content caching policy for F-RAN, where the EUs are divided into two groups, each group caching a different content set. To maximize the cache hit probability at EUs, we present a caching policy selection algorithm that allows the fog radio access point (F-AP) to choose between the proposed EU classification based content caching policy and the conventional probability based caching policy. By modeling the content request queue at each EU as an independent M/D/1 queue model at EUs, we analyze the average download delay under the proposed caching policy selection algorithm. The simulation results show that the proposed algorithm can significantly increase the cache hit probability of EUs and can also reduce the average download delay for RUs.
机译:随着移动设备和应用的快速增长,已经提出了FOG无线电接入网络(F-RAN)作为第5代移动网络的有希望的范式。同时,通过设备到设备(D2D)通信的边缘缓存可以进一步增强F-RAN,其中通过边缘缓存用户(EUS)可以减少下载延迟,而不是D2D链接到请求用户(RUS)的内容。在本文中,为了减轻有限存储在每个欧盟的影响,我们提出了一个用于F-RAN的基于EU分类的内容缓存策略,其中EUS分为两组,每个组都缓存了不同的内容集。为了最大化EUS的高速缓存命中概率,我们提出了一种缓存策略选择算法,其允许雾无线电接入点(F-AP)在所提出的基于欧盟分类的内容缓存策略和传统概率基于缓存策略之间进行选择。通过在每个欧盟将内容请求队列建模为EUS的独立M / D / 1队列模型,我们分析了所提出的缓存策略选择算法下的平均下载延迟。仿真结果表明,该算法可以显着增加EU的缓存命中概率,也可以降低RUS的平均下载延迟。

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