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An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network
Wireless Sensor Network (WSN) is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and...
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Published in: | TheScientificWorld 2016, Vol.2016 (2016), p.1-11 |
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description | Wireless Sensor Network (WSN) is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption. |
doi_str_mv | 10.1155/2016/8658760 |
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N. ; Subramanian, R.</creator><contributor>Ramachandran, Muthu</contributor><creatorcontrib>Vimalarani, C. ; Sivanandam, S. N. ; Subramanian, R. ; Ramachandran, Muthu</creatorcontrib><description>Wireless Sensor Network (WSN) is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption.</description><identifier>ISSN: 2356-6140</identifier><identifier>ISSN: 1537-744X</identifier><identifier>EISSN: 1537-744X</identifier><identifier>DOI: 10.1155/2016/8658760</identifier><identifier>PMID: 26881273</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Algorithms ; Architectural engineering ; Atoms & subatomic particles ; Clustering ; Communication ; Competition ; Computer science ; Data processing ; Data transmission ; Energy conservation ; Energy consumption ; Energy use ; Engineering ; Environmental monitoring ; Mathematical optimization ; Optimization techniques ; Power consumption ; Sensors ; Technology application ; Water levels ; Wireless networks ; Wireless sensor networks</subject><ispartof>TheScientificWorld, 2016, Vol.2016 (2016), p.1-11</ispartof><rights>Copyright © 2016 C. Vimalarani et al.</rights><rights>COPYRIGHT 2016 John Wiley & Sons, Inc.</rights><rights>Copyright © 2016 C. Vimalarani et al. 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.</rights><rights>Copyright © 2016 C. Vimalarani et al. 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4910-a0465da79a16f03bcf5e572d76062319bc339910a8917a1a9b65db9389c3b0ed3</citedby><cites>FETCH-LOGICAL-c4910-a0465da79a16f03bcf5e572d76062319bc339910a8917a1a9b65db9389c3b0ed3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1757628814/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1757628814?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,4024,25753,27923,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26881273$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Ramachandran, Muthu</contributor><creatorcontrib>Vimalarani, C.</creatorcontrib><creatorcontrib>Sivanandam, S. N.</creatorcontrib><creatorcontrib>Subramanian, R.</creatorcontrib><title>An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network</title><title>TheScientificWorld</title><addtitle>ScientificWorldJournal</addtitle><description>Wireless Sensor Network (WSN) is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption.</description><subject>Algorithms</subject><subject>Architectural engineering</subject><subject>Atoms & subatomic particles</subject><subject>Clustering</subject><subject>Communication</subject><subject>Competition</subject><subject>Computer science</subject><subject>Data processing</subject><subject>Data transmission</subject><subject>Energy conservation</subject><subject>Energy consumption</subject><subject>Energy use</subject><subject>Engineering</subject><subject>Environmental monitoring</subject><subject>Mathematical optimization</subject><subject>Optimization techniques</subject><subject>Power consumption</subject><subject>Sensors</subject><subject>Technology application</subject><subject>Water levels</subject><subject>Wireless networks</subject><subject>Wireless sensor networks</subject><issn>2356-6140</issn><issn>1537-744X</issn><issn>1537-744X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqNksFv0zAUxiMEYmVw44wicUGCbHYc2_EFqVQDJk0UaSAQF-vFeUldErvYKdP463FpGYwT8sH2e7_32c_-suwxJSeUcn5aEipOa8FrKcidbEY5k4Wsqs93s1nJuCgErchR9iDGNSGslpTfz45KUde0lGyWfZm7_MytwBls8_eXy-IVxLRaDNs4YbCuT1kM_XW-3Ex2tD9gst7l86H3wU6rMe98yD_ZgAPGmF-ii2n_DqcrH74-zO51MER8dJiPs4-vzz4s3hYXyzfni_lFYSpFSQGkErwFqYCKjrDGdBy5LNvUjigZVY1hTCUQakUlUFBNwhvFamVYQ7Blx9n5Xrf1sNabYEcI19qD1b8CPvQawmTNgLo0rayAcoUNqUpsgTIA3snO1C1B4Enr5V5rs21GbA26KcBwS_R2xtmV7v13XUkmFJFJ4NlBIPhvW4yTHm00OAzg0G-jplLw1IdiVUKf_oOu_Ta49FSJ4lKU6Y921Mme6iE1YF3n07kmjRZHa7zDzqb4nFNCKRGcpIIX-wITfIwBu5vbU6J3jtE7x-iDYxL-5O-Ob-DfFknA8z2wsq6FK_ufcpgY7OAPTcv0n4r9BBeE0a0</recordid><startdate>2016</startdate><enddate>2016</enddate><creator>Vimalarani, C.</creator><creator>Sivanandam, S. 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subjects | Algorithms Architectural engineering Atoms & subatomic particles Clustering Communication Competition Computer science Data processing Data transmission Energy conservation Energy consumption Energy use Engineering Environmental monitoring Mathematical optimization Optimization techniques Power consumption Sensors Technology application Water levels Wireless networks Wireless sensor networks |
title | An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network |
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