2020•Unpublished venueRequires access

CPNDD:Content Placement Approach in Content Centric Networking

Sumit Kumar, Rajeev Tiwari, Mohammad S. Obaidat, Neeraj Kumar, Kuei-Fang Hsiao

Open publisher page 12 citations

Abstract

Content Centric Networks (CCN) has been evolved as a promising internet architecture that focuses on content centric approach for content requests rather than host centric approach. CCN provide in-network caching and content distribution capability improves Quality-of-Service by reducing intermediatory hop count and server load, which condequently reduces bandwidth requirements. Existing work in CCN emphasis on minimizing content caching operations and maximizing network hit ratio. In this paper, we have investigated the effect of in-network caching based on content provider distance and node centrality parameters over network hit ratio. A novel content placement approach named CPNDD (Content Placement based on Normalized Node Degree and Distance), has been proposed that collectively implement both parameters to intelligently select caching location in the network to maximize gain in hit ratio. The weightage of both parameters has been computed using extensive simulation on abilene network topology. We have compared our scheme with several peer caching algorithms in CCN. Simulation results are obtained for different cache size, exponent value of zipf distribution and number of requests. The results demonstrate that CPNDD increases in-network hit ratio gain upto 40% as comparison to existing algorithms.

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What this paper is about

Content Centric Networks (CCN) has been evolved as a promising internet architecture that focuses on content centric approach for content requests rather than host centric approach. CCN provide in-network caching and content distribution capability improves Quality-of-Service by reducing intermediatory hop count and server load, which condequently reduces bandwidth requirements. Existing work in CCN emphasis on minimizing content caching operations and maximizing network hit ratio. In this paper, we have investigated the effect of in-network caching based on content provider distance and node centrality parameters over network hit ratio. A novel content placement approach named CPNDD (Content Placement based on Normalized Node Degree and Distance), has been proposed that collectively implement both parameters to intelligently select caching location in the network to maximize gain in hit ratio. The weightage of both parameters has been computed using extensive simulation on abilene network topology. We have compared our scheme with several peer caching algorithms in CCN. Simulation results are obtained for different cache size, exponent value of zipf distribution and number of requests. The results demonstrate that CPNDD increases in-network hit ratio gain upto 40% as comparison to existing algorithms.

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Available abstract

Content Centric Networks (CCN) has been evolved as a promising internet architecture that focuses on content centric approach for content requests rather than host centric approach. CCN provide in-network caching and content distribution capability improves Quality-of-Service by reducing intermediatory hop count and server load, which condequently reduces bandwidth requirements. Existing work in CCN emphasis on minimizing content caching operations and maximizing network hit ratio. In this paper, we have investigated the effect of in-network caching based on content provider distance and node centrality parameters over network hit ratio. A novel content placement approach named CPNDD (Content Placement based on Normalized Node Degree and Distance), has been proposed that collectively implement both parameters to intelligently select caching location in the network to maximize gain in hit ratio. The weightage of both parameters has been computed using extensive simulation on abilene network topology. We have compared our scheme with several peer caching algorithms in CCN. Simulation results are obtained for different cache size, exponent value of zipf distribution and number of requests. The results demonstrate that CPNDD increases in-network hit ratio gain upto 40% as comparison to existing algorithms.

Key concepts: Content centric networking, Computer science, Information-centric networking, Computer network, Cache, Zipf's law, Network topology, The Internet

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