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Information Centric Modeling for Two-tier Cache Enabled Cellular Networks

机译:支持双层缓存的蜂窝网络的信息中心建模

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摘要

In this article, we introduce a new metric called `information centric coverage probability' to characterize the performance of a two-tier cache enabled cellular network. The proposed metric unifies the dynamics of in-network caching and heterogeneous networking to provide a unified performance measure. Specifically, it quantifies the probability that a mobile user (MU) is covered at a desired rate when a certain content is requested from a global content library. In other words, it quantifies the percentage of time when an MU can be served locally without paying the traffic penalties at backhaul, fronthaul and core networks. Caching dynamics are modeled by considering that the content which is least recently used (LRU) is evicted while the requested content is stored in the cache. The considered two-tier cellular model leverages coordination between the macro base-station (MBS) and the small cell base-stations (SBSs) to maximize the resource efficiency. More specifically, coordination between macro and small cells enables an arbitrary SBS to exploit the caches at other SBSs in the neighborhood. Thus reducing the requirement for huge and expensive memory modules at individual SBSs. The spatial dynamics of cellular network are modeled by borrowing well established tools from stochastic geometry. Propagation uncertainties are explicitly factored in characterization by considering the small scale Rayleigh fading and the large scale power-law path-loss model. It is shown that the information centric coverage probability is a function of (i) the size of caches at the SBSs and the MBS; (ii) the content eviction strategy; (iii) the underlying popularity law for referenced objects; (iv) the size of the global content library; (v) desired downlink transmission rate; (vi) the amount of spectrum allocated to each tier; (vii) pathloss exponent; and (viii) the deployment density of the SBSs and the MBSs. Our analysis reveals that significant performance gains can be harnessed with appropriate dimensioning of both cache sizes and deployment density. Finally, identification of memory limited vs. QoS limited operational regime for two-tier cellular networks is considered.
机译:在本文中,我们介绍了一种称为“以信息为中心的覆盖率”的新指标,以表征支持两层缓存的蜂窝网络的性能。提出的度量标准统一了网络内缓存和异构网络的动态特性,以提供统一的性能度量。具体地,当从全局内容库请求某个内容时,它量化以期望的速率覆盖移动用户(MU)的概率。换句话说,它量化了MU可以在本地服务而不用支付回程,前程和核心网流量损失的时间百分比。通过考虑在将请求的内容存储在缓存中时逐出最近最少使用的内容(LRU)来对缓存动态进行建模。所考虑的两层蜂窝模型利用了宏基站(MBS)和小蜂窝基站(SBS)之间的协调,以最大化资源效率。更具体地说,宏小区和小小区之间的协调使得任意SBS能够利用附近其他SBS的缓存。因此,减少了单个SBS对庞大而昂贵的存储模块的需求。蜂窝网络的空间动力学是通过从随机几何学中借鉴成熟的工具来建模的。通过考虑小规模瑞利衰落和大规模幂律路径损耗模型,可以明确地将传播不确定性因素纳入特征分析。结果表明,以信息为中心的覆盖概率是(i)SBS和MBS处的高速缓存大小的函数; (ii)内容驱逐策略; (iii)引用对象的基本流行法; (iv)全球内容库的规模; (v)期望的下行链路传输速率; (vi)分配给每一层的频谱数量; (vii)路径损耗指数; (viii)SBS和MBS的部署密度。我们的分析表明,通过适当地确定缓存大小和部署密度,可以利用显着的性能提升。最后,考虑了识别两层蜂窝网络的存储器受限与QoS受限的操作方案。

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