Universal Caching Model and Markov-based cache analysis for Information Centric Networks

Universal Caching Model and Markov-based cache analysis for Information Centric Networks Information Centric Networks (ICN) is proposed as an alternative design for content-based communication rather than host-to-host-based communication. In ICN architecture, the data are cached or stored at intermediate routers to satisfy future demands locally without repeatedly getting it from the original source. For ICN architecture to work efficiently, caching policies must be defined such that most of the requests are satisfied locally. In this paper, we propose Universal Caching, a novel caching algorithm which takes into account multiple parameters like distance from the content source, frequency of fetching the content, number of outgoing links at the intermediate router. We further propose a discrete time Markov model and entropy-based analysis to determine the cache size for a given cache hit requirement at a router in ICN networks. We have also established that Universal Caching policy is in fact an optimal caching policy and have calculated the bounds for the same as well. To validate the proposed caching policy and the analytical model, we have conducted extensive MATLAB-based simulations. Our simulation results show that the Universal Caching outperforms other caching policies like Least Recently Used, First In, First Out in terms of cache hits, access delay, etc. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Photonic Network Communications Springer Journals

Universal Caching Model and Markov-based cache analysis for Information Centric Networks

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Springer US
Copyright © 2015 by Springer Science+Business Media New York
Computer Science; Computer Communication Networks; Electrical Engineering; Characterization and Evaluation of Materials
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