Dynamic Overlapping Clustering for Wireless Sensor Networks Based-on Particle Swarm Optimization

<p class="Abstract"><span lang="EN-US">In the recent years, Wireless Sensor Network (WSN</span><!--[if supportFields]><span lang=EN-US><span style='mso-element: field-begin'></span> XE &quot;WSN&quot; </span><!...

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Main Authors: Amin Suharjono, Wirawan Wirawan, Gamantyo Hendrantoro
Format: Article
Language:English
Published: ITB Journal Publisher 2013-09-01
Series:Journal of ICT Research and Applications
Online Access:http://journals.itb.ac.id/index.php/jictra/article/view/220
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author Amin Suharjono
Wirawan Wirawan
Gamantyo Hendrantoro
author_facet Amin Suharjono
Wirawan Wirawan
Gamantyo Hendrantoro
author_sort Amin Suharjono
collection DOAJ
description <p class="Abstract"><span lang="EN-US">In the recent years, Wireless Sensor Network (WSN</span><!--[if supportFields]><span lang=EN-US><span style='mso-element: field-begin'></span> XE &quot;WSN&quot; </span><![endif]--><!--[if supportFields]><span lang=EN-US><span style='mso-element:field-end'></span></span><![endif]--><span lang="EN-US">) has been one of the most interesting research topics because of its flexibility and many potential applications. However, in the applications, there are still resources constraints, including: energy, computation, and bandwidth. It is believed that clustering</span><!--[if supportFields]><span lang=EN-US><span style='mso-element:field-begin'></span> XE &quot;clustering&quot; </span><![endif]--><!--[if supportFields]><span lang=EN-US><span style='mso-element:field-end'></span></span><![endif]--><span lang="EN-US"> is the best solution for the need of energy efficiency and scalability. In order to reach the high level of energy efficiencies, mostly, the clustering algorithms avoid the possibility of overlap between clusters. But in fact, there are several applications that need the occurrence of overlaps between clusters. In this paper, we propose a Particle Swarm Optimization (PSO</span><!--[if supportFields]><span lang=EN-US><span style='mso-element:field-begin'></span> XE &quot;PSO&quot; </span><![endif]--><!--[if supportFields]><span lang=EN-US><span style='mso-element:field-end'></span></span><![endif]--><span lang="EN-US">)-based Clustering algorithm that has capability to control the overlap between clusters but still it has an ability to reach energy efficiency. PSO is chosen because it has a light computation and can quickly reach convergence. This proposed algorithm performance is analytically and experimentally compared with clustering on LEACH. The result of the test shows that this proposed algorithm has a capability to control the rate of overlapping</span><!--[if supportFields]><span lang=EN-US><span style='mso-element:field-begin'></span> XE &quot;overlapping&quot; </span><![endif]--><!--[if supportFields]><span lang=EN-US><span style='mso-element:field-end'></span></span><![endif]--><span lang="EN-US"> degree linearly. The testing on the PSO for clustering also shows the better performance than on LEACH, although there are a few problems related to its complexity.</span></p>
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spelling doaj.art-a34f3d2a75474ee385c375ca84d8ce382022-12-21T22:08:50ZengITB Journal PublisherJournal of ICT Research and Applications2337-57872338-54992013-09-01614362221Dynamic Overlapping Clustering for Wireless Sensor Networks Based-on Particle Swarm OptimizationAmin Suharjono0Wirawan Wirawan1Gamantyo Hendrantoro2Electrical Engineering Dept., Institut Teknologi Sepuluh Nopember (ITS) Surabaya 60111, Indonesia Electrical Engineering Dept., Politeknik Negeri Semarang (POLINES) Semarang 50275, IndonesiaElectrical Engineering Dept., Institut Teknologi Sepuluh Nopember (ITS) Surabaya 60111, IndonesiaElectrical Engineering Dept., Institut Teknologi Sepuluh Nopember (ITS) Surabaya 60111, Indonesia<p class="Abstract"><span lang="EN-US">In the recent years, Wireless Sensor Network (WSN</span><!--[if supportFields]><span lang=EN-US><span style='mso-element: field-begin'></span> XE &quot;WSN&quot; </span><![endif]--><!--[if supportFields]><span lang=EN-US><span style='mso-element:field-end'></span></span><![endif]--><span lang="EN-US">) has been one of the most interesting research topics because of its flexibility and many potential applications. However, in the applications, there are still resources constraints, including: energy, computation, and bandwidth. It is believed that clustering</span><!--[if supportFields]><span lang=EN-US><span style='mso-element:field-begin'></span> XE &quot;clustering&quot; </span><![endif]--><!--[if supportFields]><span lang=EN-US><span style='mso-element:field-end'></span></span><![endif]--><span lang="EN-US"> is the best solution for the need of energy efficiency and scalability. In order to reach the high level of energy efficiencies, mostly, the clustering algorithms avoid the possibility of overlap between clusters. But in fact, there are several applications that need the occurrence of overlaps between clusters. In this paper, we propose a Particle Swarm Optimization (PSO</span><!--[if supportFields]><span lang=EN-US><span style='mso-element:field-begin'></span> XE &quot;PSO&quot; </span><![endif]--><!--[if supportFields]><span lang=EN-US><span style='mso-element:field-end'></span></span><![endif]--><span lang="EN-US">)-based Clustering algorithm that has capability to control the overlap between clusters but still it has an ability to reach energy efficiency. PSO is chosen because it has a light computation and can quickly reach convergence. This proposed algorithm performance is analytically and experimentally compared with clustering on LEACH. The result of the test shows that this proposed algorithm has a capability to control the rate of overlapping</span><!--[if supportFields]><span lang=EN-US><span style='mso-element:field-begin'></span> XE &quot;overlapping&quot; </span><![endif]--><!--[if supportFields]><span lang=EN-US><span style='mso-element:field-end'></span></span><![endif]--><span lang="EN-US"> degree linearly. The testing on the PSO for clustering also shows the better performance than on LEACH, although there are a few problems related to its complexity.</span></p>http://journals.itb.ac.id/index.php/jictra/article/view/220
spellingShingle Amin Suharjono
Wirawan Wirawan
Gamantyo Hendrantoro
Dynamic Overlapping Clustering for Wireless Sensor Networks Based-on Particle Swarm Optimization
Journal of ICT Research and Applications
title Dynamic Overlapping Clustering for Wireless Sensor Networks Based-on Particle Swarm Optimization
title_full Dynamic Overlapping Clustering for Wireless Sensor Networks Based-on Particle Swarm Optimization
title_fullStr Dynamic Overlapping Clustering for Wireless Sensor Networks Based-on Particle Swarm Optimization
title_full_unstemmed Dynamic Overlapping Clustering for Wireless Sensor Networks Based-on Particle Swarm Optimization
title_short Dynamic Overlapping Clustering for Wireless Sensor Networks Based-on Particle Swarm Optimization
title_sort dynamic overlapping clustering for wireless sensor networks based on particle swarm optimization
url http://journals.itb.ac.id/index.php/jictra/article/view/220
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AT wirawanwirawan dynamicoverlappingclusteringforwirelesssensornetworksbasedonparticleswarmoptimization
AT gamantyohendrantoro dynamicoverlappingclusteringforwirelesssensornetworksbasedonparticleswarmoptimization