Analytical Modelling of Content Transfer in Information Centric Networks

Han Xu, Haozhe Wang, Jia Hu, G. Min
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Abstract

The proliferation of advanced information technology applications such as Virtual/Augmented Reality and ultra-high-definition (UHD) multimedia services that demand high bandwidth and ultra-low latency put tremendous pressure on the current communication networks. To meet these pressing requirements, Information-Centric Networks (ICN), a promising future Internet paradigm has been attracting much research attention. ICN deploy ubiquitous in-network caching that could not only handle large content dissemination and retrieval but also expedite the content delivery. To investigate the performance of ICN, it is important to have an analytical model that can accurately characterize the content transfer in ICN under different network and traffic conditions. In this paper, we exploit the queueing network theory to develop a new analytical model for content transfer in ICN. We derive the mathematical expressions for calculating cache miss rate and content delivery time. The accuracy of our analytical model is validated by comparing the analytical results with those obtained from simulation experiments. We also use the model to investigate the content delivery time under various network and traffic conditions.
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信息中心网络中内容转移的分析建模
随着虚拟/增强现实(vr)和超高清(UHD)多媒体等先进信息技术应用的激增,需要高带宽和超低延迟,给当前的通信网络带来了巨大的压力。为了满足这些迫切的需求,信息中心网络(ICN)作为一种很有前途的未来互联网模式已经引起了人们的广泛关注。ICN部署了无处不在的网络缓存,不仅可以处理大量内容的传播和检索,还可以加快内容的传递。为了研究ICN的性能,重要的是要有一个分析模型,可以准确地表征不同网络和流量条件下ICN中的内容传输。本文利用排队网络理论建立了一个新的ICN内容迁移分析模型。导出了计算缓存缺失率和内容传递时间的数学表达式。通过与仿真实验结果的比较,验证了分析模型的准确性。我们还使用该模型研究了不同网络和流量条件下的内容交付时间。
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