A Survey on Node Clustering in Cognitive Radio Wireless Sensor Networks

Cognitive radio wireless sensor networks (CR-WSNs) have attracted a great deal of attention recently due to the emerging spectrum scarcity issue. This work attempts to provide a detailed analysis of the role of node clustering in CR-WSNs. We outline the objectives, requirements, and advantages of no...

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Detalles Bibliográficos
Autores principales: Joshi, Gyanendra Prasad, Kim, Sung Won
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5038743/
https://www.ncbi.nlm.nih.gov/pubmed/27626421
http://dx.doi.org/10.3390/s16091465
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author Joshi, Gyanendra Prasad
Kim, Sung Won
author_facet Joshi, Gyanendra Prasad
Kim, Sung Won
author_sort Joshi, Gyanendra Prasad
collection PubMed
description Cognitive radio wireless sensor networks (CR-WSNs) have attracted a great deal of attention recently due to the emerging spectrum scarcity issue. This work attempts to provide a detailed analysis of the role of node clustering in CR-WSNs. We outline the objectives, requirements, and advantages of node clustering in CR-WSNs. We describe how a CR-WSN with node clustering differs from conventional wireless sensor networks, and we discuss its characteristics, architecture, and topologies. We survey the existing clustering algorithms and compare their objectives and features. We suggest how clustering issues and challenges can be handled.
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spelling pubmed-50387432016-09-29 A Survey on Node Clustering in Cognitive Radio Wireless Sensor Networks Joshi, Gyanendra Prasad Kim, Sung Won Sensors (Basel) Review Cognitive radio wireless sensor networks (CR-WSNs) have attracted a great deal of attention recently due to the emerging spectrum scarcity issue. This work attempts to provide a detailed analysis of the role of node clustering in CR-WSNs. We outline the objectives, requirements, and advantages of node clustering in CR-WSNs. We describe how a CR-WSN with node clustering differs from conventional wireless sensor networks, and we discuss its characteristics, architecture, and topologies. We survey the existing clustering algorithms and compare their objectives and features. We suggest how clustering issues and challenges can be handled. MDPI 2016-09-10 /pmc/articles/PMC5038743/ /pubmed/27626421 http://dx.doi.org/10.3390/s16091465 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Joshi, Gyanendra Prasad
Kim, Sung Won
A Survey on Node Clustering in Cognitive Radio Wireless Sensor Networks
title A Survey on Node Clustering in Cognitive Radio Wireless Sensor Networks
title_full A Survey on Node Clustering in Cognitive Radio Wireless Sensor Networks
title_fullStr A Survey on Node Clustering in Cognitive Radio Wireless Sensor Networks
title_full_unstemmed A Survey on Node Clustering in Cognitive Radio Wireless Sensor Networks
title_short A Survey on Node Clustering in Cognitive Radio Wireless Sensor Networks
title_sort survey on node clustering in cognitive radio wireless sensor networks
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5038743/
https://www.ncbi.nlm.nih.gov/pubmed/27626421
http://dx.doi.org/10.3390/s16091465
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