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Energy Aware Swarm Optimization with Intercluster Search for Wireless Sensor Network

Wireless sensor networks (WSNs) are emerging as a low cost popular solution for many real-world challenges. The low cost ensures deployment of large sensor arrays to perform military and civilian tasks. Generally, WSNs are power constrained due to their unique deployment method which makes replaceme...

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Autores principales: Thilagavathi, Shanmugasundaram, Gnanasambandan Geetha, Bhavani
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4396544/
https://www.ncbi.nlm.nih.gov/pubmed/25918741
http://dx.doi.org/10.1155/2015/395256
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author Thilagavathi, Shanmugasundaram
Gnanasambandan Geetha, Bhavani
author_facet Thilagavathi, Shanmugasundaram
Gnanasambandan Geetha, Bhavani
author_sort Thilagavathi, Shanmugasundaram
collection PubMed
description Wireless sensor networks (WSNs) are emerging as a low cost popular solution for many real-world challenges. The low cost ensures deployment of large sensor arrays to perform military and civilian tasks. Generally, WSNs are power constrained due to their unique deployment method which makes replacement of battery source difficult. Challenges in WSN include a well-organized communication platform for the network with negligible power utilization. In this work, an improved binary particle swarm optimization (PSO) algorithm with modified connected dominating set (CDS) based on residual energy is proposed for discovery of optimal number of clusters and cluster head (CH). Simulations show that the proposed BPSO-T and BPSO-EADS perform better than LEACH- and PSO-based system in terms of energy savings and QOS.
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spelling pubmed-43965442015-04-27 Energy Aware Swarm Optimization with Intercluster Search for Wireless Sensor Network Thilagavathi, Shanmugasundaram Gnanasambandan Geetha, Bhavani ScientificWorldJournal Research Article Wireless sensor networks (WSNs) are emerging as a low cost popular solution for many real-world challenges. The low cost ensures deployment of large sensor arrays to perform military and civilian tasks. Generally, WSNs are power constrained due to their unique deployment method which makes replacement of battery source difficult. Challenges in WSN include a well-organized communication platform for the network with negligible power utilization. In this work, an improved binary particle swarm optimization (PSO) algorithm with modified connected dominating set (CDS) based on residual energy is proposed for discovery of optimal number of clusters and cluster head (CH). Simulations show that the proposed BPSO-T and BPSO-EADS perform better than LEACH- and PSO-based system in terms of energy savings and QOS. Hindawi Publishing Corporation 2015 2015-03-30 /pmc/articles/PMC4396544/ /pubmed/25918741 http://dx.doi.org/10.1155/2015/395256 Text en Copyright © 2015 S. Thilagavathi and B. Gnanasambandan Geetha. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Thilagavathi, Shanmugasundaram
Gnanasambandan Geetha, Bhavani
Energy Aware Swarm Optimization with Intercluster Search for Wireless Sensor Network
title Energy Aware Swarm Optimization with Intercluster Search for Wireless Sensor Network
title_full Energy Aware Swarm Optimization with Intercluster Search for Wireless Sensor Network
title_fullStr Energy Aware Swarm Optimization with Intercluster Search for Wireless Sensor Network
title_full_unstemmed Energy Aware Swarm Optimization with Intercluster Search for Wireless Sensor Network
title_short Energy Aware Swarm Optimization with Intercluster Search for Wireless Sensor Network
title_sort energy aware swarm optimization with intercluster search for wireless sensor network
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4396544/
https://www.ncbi.nlm.nih.gov/pubmed/25918741
http://dx.doi.org/10.1155/2015/395256
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