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Effect of optimal cluster head placement in MANET through multi objective GA
Ad-hoc network refers to a wireless network comprising of non-stationary nodes, which autonomously collaborate between themselves for transmitting communication. Wireless sensor networks (WSN) are a subclass, where the nodes feature topological limitation in creating contact with the outside world....
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creator | Sett, Sujoy Thakurta, Parag Kumar Guha |
description | Ad-hoc network refers to a wireless network comprising of non-stationary nodes, which autonomously collaborate between themselves for transmitting communication. Wireless sensor networks (WSN) are a subclass, where the nodes feature topological limitation in creating contact with the outside world. Replenishment of energy in WSN is usually not possible due to inhospitable environment. Accordingly, activity switching and clustering are two major approaches adopted for energy conservation and prolonging lifetime in MANETs. For large networks, soft computing has been repeatedly proven to achieve near to optimal solutions in routing and clustering problems. A genetic algorithm based approach towards efficient election of cluster heads has been proposed. The objective functions targeting optimal selection and placement of cluster centers has been derived. The problem is genetically encoded and standard multi-objective genetic algorithm is used for evaluation. Subsequent results and comparative discussion is provided. |
doi_str_mv | 10.1109/ICACEA.2015.7164819 |
format | conference_proceeding |
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Wireless sensor networks (WSN) are a subclass, where the nodes feature topological limitation in creating contact with the outside world. Replenishment of energy in WSN is usually not possible due to inhospitable environment. Accordingly, activity switching and clustering are two major approaches adopted for energy conservation and prolonging lifetime in MANETs. For large networks, soft computing has been repeatedly proven to achieve near to optimal solutions in routing and clustering problems. A genetic algorithm based approach towards efficient election of cluster heads has been proposed. The objective functions targeting optimal selection and placement of cluster centers has been derived. The problem is genetically encoded and standard multi-objective genetic algorithm is used for evaluation. 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Wireless sensor networks (WSN) are a subclass, where the nodes feature topological limitation in creating contact with the outside world. Replenishment of energy in WSN is usually not possible due to inhospitable environment. Accordingly, activity switching and clustering are two major approaches adopted for energy conservation and prolonging lifetime in MANETs. For large networks, soft computing has been repeatedly proven to achieve near to optimal solutions in routing and clustering problems. A genetic algorithm based approach towards efficient election of cluster heads has been proposed. The objective functions targeting optimal selection and placement of cluster centers has been derived. The problem is genetically encoded and standard multi-objective genetic algorithm is used for evaluation. Subsequent results and comparative discussion is provided.</description><subject>base station</subject><subject>cluster head</subject><subject>clustering</subject><subject>Genetic algorithms</subject><subject>Genetics</subject><subject>MANET</subject><subject>Mobile ad hoc networks</subject><subject>mobile node</subject><subject>MOGA</subject><subject>MOO</subject><subject>routing</subject><subject>Sociology</subject><subject>Statistics</subject><subject>Wireless sensor networks</subject><subject>WSN</subject><isbn>146736911X</isbn><isbn>9781467369114</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2015</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotj81OhDAURuvCRB3nCWbTFwB729KfJSE4mqBuxsTdpIVbYQIDgWLi2zuJs_pW5-R8hOyApQDMPr0WeVHmKWeQpRqUNGBvyANIpYWyAF93ZLssJ8YYaKWlNPekKkPAOtIx0HGK3eB6WvfrEnGmLbqGTr2rccBzpN2ZvuXv5YHGdh7X75YOax87OvrThe9-kO7zR3IbXL_g9rob8vlcHoqXpPrYX9KqpOPMxAS8F03gMmNeeWGUabTBjLngOHgEzdAYbjMPumbc6KCN8T6I2gSwUtpMbMju39sh4nGaL9nz7_F6WPwB84VLbQ</recordid><startdate>20150301</startdate><enddate>20150301</enddate><creator>Sett, Sujoy</creator><creator>Thakurta, Parag Kumar Guha</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20150301</creationdate><title>Effect of optimal cluster head placement in MANET through multi objective GA</title><author>Sett, Sujoy ; Thakurta, Parag Kumar Guha</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i208t-1bb3df2450b6b3868d78e50afa21be170e88295b17c0287f788bbf3c8f1944953</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2015</creationdate><topic>base station</topic><topic>cluster head</topic><topic>clustering</topic><topic>Genetic algorithms</topic><topic>Genetics</topic><topic>MANET</topic><topic>Mobile ad hoc networks</topic><topic>mobile node</topic><topic>MOGA</topic><topic>MOO</topic><topic>routing</topic><topic>Sociology</topic><topic>Statistics</topic><topic>Wireless sensor networks</topic><topic>WSN</topic><toplevel>online_resources</toplevel><creatorcontrib>Sett, Sujoy</creatorcontrib><creatorcontrib>Thakurta, Parag Kumar Guha</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Sett, Sujoy</au><au>Thakurta, Parag Kumar Guha</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Effect of optimal cluster head placement in MANET through multi objective GA</atitle><btitle>2015 International Conference on Advances in Computer Engineering and Applications</btitle><stitle>ICACEA</stitle><date>2015-03-01</date><risdate>2015</risdate><spage>832</spage><epage>837</epage><pages>832-837</pages><eisbn>146736911X</eisbn><eisbn>9781467369114</eisbn><abstract>Ad-hoc network refers to a wireless network comprising of non-stationary nodes, which autonomously collaborate between themselves for transmitting communication. Wireless sensor networks (WSN) are a subclass, where the nodes feature topological limitation in creating contact with the outside world. Replenishment of energy in WSN is usually not possible due to inhospitable environment. Accordingly, activity switching and clustering are two major approaches adopted for energy conservation and prolonging lifetime in MANETs. For large networks, soft computing has been repeatedly proven to achieve near to optimal solutions in routing and clustering problems. A genetic algorithm based approach towards efficient election of cluster heads has been proposed. The objective functions targeting optimal selection and placement of cluster centers has been derived. The problem is genetically encoded and standard multi-objective genetic algorithm is used for evaluation. Subsequent results and comparative discussion is provided.</abstract><pub>IEEE</pub><doi>10.1109/ICACEA.2015.7164819</doi><tpages>6</tpages></addata></record> |
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subjects | base station cluster head clustering Genetic algorithms Genetics MANET Mobile ad hoc networks mobile node MOGA MOO routing Sociology Statistics Wireless sensor networks WSN |
title | Effect of optimal cluster head placement in MANET through multi objective GA |
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