QoS Improvement Using In-Network Caching Based on Clustering and Popularity Heuristics in CCN

Content-Centric Networking (CCN) has emerged as a potential Internet architecture that supports name-based content retrieval mechanism in contrast to the current host location-oriented IP architecture. The in-network caching capability of CCN ensures higher content availability, lesser network delay...

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Autores principales:	Sumit Kumar, Rajeev Tiwari, Wei-Chiang Hong
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	content-centric networking content caching network clustering content popularity Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/cce0b73a26de41a5bd35040e023bb9ec
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id	oai:doaj.org-article:cce0b73a26de41a5bd35040e023bb9ec
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spelling	oai:doaj.org-article:cce0b73a26de41a5bd35040e023bb9ec2021-11-11T19:11:12ZQoS Improvement Using In-Network Caching Based on Clustering and Popularity Heuristics in CCN10.3390/s212172041424-8220https://doaj.org/article/cce0b73a26de41a5bd35040e023bb9ec2021-10-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7204https://doaj.org/toc/1424-8220Content-Centric Networking (CCN) has emerged as a potential Internet architecture that supports name-based content retrieval mechanism in contrast to the current host location-oriented IP architecture. The in-network caching capability of CCN ensures higher content availability, lesser network delay, and leads to server load reduction. It was observed that caching the contents on each intermediate node does not use the network resources efficiently. Hence, efficient content caching decisions are crucial to improve the Quality-of-Service (QoS) for the end-user devices and improved network performance. Towards this, a novel content caching scheme is proposed in this paper. The proposed scheme first clusters the network nodes based on the hop count and bandwidth parameters to reduce content redundancy and caching operations. Then, the scheme takes content placement decisions using the cluster information, content popularity, and the hop count parameters, where the caching probability improves as the content traversed toward the requester. Hence, using the proposed heuristics, the popular contents are placed near the edges of the network to achieve a high cache hit ratio. Once the cache becomes full, the scheme implements Least-Frequently-Used (LFU) replacement scheme to substitute the least accessed content in the network routers. Extensive simulations are conducted and the performance of the proposed scheme is investigated under different network parameters that demonstrate the superiority of the proposed strategy <i>w.r.t</i> the peer competing strategies.Sumit KumarRajeev TiwariWei-Chiang HongMDPI AGarticlecontent-centric networkingcontent cachingnetwork clusteringcontent popularityChemical technologyTP1-1185ENSensors, Vol 21, Iss 7204, p 7204 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	content-centric networking content caching network clustering content popularity Chemical technology TP1-1185
spellingShingle	content-centric networking content caching network clustering content popularity Chemical technology TP1-1185 Sumit Kumar Rajeev Tiwari Wei-Chiang Hong QoS Improvement Using In-Network Caching Based on Clustering and Popularity Heuristics in CCN
description	Content-Centric Networking (CCN) has emerged as a potential Internet architecture that supports name-based content retrieval mechanism in contrast to the current host location-oriented IP architecture. The in-network caching capability of CCN ensures higher content availability, lesser network delay, and leads to server load reduction. It was observed that caching the contents on each intermediate node does not use the network resources efficiently. Hence, efficient content caching decisions are crucial to improve the Quality-of-Service (QoS) for the end-user devices and improved network performance. Towards this, a novel content caching scheme is proposed in this paper. The proposed scheme first clusters the network nodes based on the hop count and bandwidth parameters to reduce content redundancy and caching operations. Then, the scheme takes content placement decisions using the cluster information, content popularity, and the hop count parameters, where the caching probability improves as the content traversed toward the requester. Hence, using the proposed heuristics, the popular contents are placed near the edges of the network to achieve a high cache hit ratio. Once the cache becomes full, the scheme implements Least-Frequently-Used (LFU) replacement scheme to substitute the least accessed content in the network routers. Extensive simulations are conducted and the performance of the proposed scheme is investigated under different network parameters that demonstrate the superiority of the proposed strategy <i>w.r.t</i> the peer competing strategies.
format	article
author	Sumit Kumar Rajeev Tiwari Wei-Chiang Hong
author_facet	Sumit Kumar Rajeev Tiwari Wei-Chiang Hong
author_sort	Sumit Kumar
title	QoS Improvement Using In-Network Caching Based on Clustering and Popularity Heuristics in CCN
title_short	QoS Improvement Using In-Network Caching Based on Clustering and Popularity Heuristics in CCN
title_full	QoS Improvement Using In-Network Caching Based on Clustering and Popularity Heuristics in CCN
title_fullStr	QoS Improvement Using In-Network Caching Based on Clustering and Popularity Heuristics in CCN
title_full_unstemmed	QoS Improvement Using In-Network Caching Based on Clustering and Popularity Heuristics in CCN
title_sort	qos improvement using in-network caching based on clustering and popularity heuristics in ccn
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/cce0b73a26de41a5bd35040e023bb9ec
work_keys_str_mv	AT sumitkumar qosimprovementusinginnetworkcachingbasedonclusteringandpopularityheuristicsinccn AT rajeevtiwari qosimprovementusinginnetworkcachingbasedonclusteringandpopularityheuristicsinccn AT weichianghong qosimprovementusinginnetworkcachingbasedonclusteringandpopularityheuristicsinccn
_version_	1718431611504033792

QoS Improvement Using In-Network Caching Based on Clustering and Popularity Heuristics in CCN

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