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An energy efficient Genetic Algorithm based approach for sensor-to-sink binding in multi-sink wireless sensor networks

Show simple item record Safa H. Moussa M. Artail H.
dc.contributor.editor 2014 2017-09-07T07:08:28Z 2017-09-07T07:08:28Z 2014
dc.identifier 10.1007/s11276-013-0600-2
dc.identifier.issn 10220038
dc.description.abstract Wireless sensor networks (WSNs) are ad-hoc networks in which sensors, that are designed to relay data back to sink nodes and-or Base Stations, are deployed in an area and may be configured in real time. Sensors, however, have limited energy supplies and are often left untouched after deployment, thus making battery replacement very difficult or even impossible. Therefore, energy should be efficiently conserved to extend the WSNs lifetime. One of the existing solutions is to deploy multiple sinks, more capable nodes in comparison to sensors, in the network to increase the coverage area and shorten the communication distance between sensors and sinks. However, this raises the issue concerning which sensors should bind to which sinks in order to avoid overloading particular sinks. In this paper, we devise a Genetic Algorithm based approach to solve the problem of balancing the load of sensors amongst sinks in a multi-sink WSN, while ensuring that the best routes to sinks are found for the sensors that cannot directly reach a sink. We evaluate the performance of our approach and compare it to an existing one using the network simulator NS-2 through measuring several metrics such as the variance of remaining energy among sinks, and energy consumption in sinks. The obtained results show that the proposed approach promising. © Springer Science+Business Media New York 2013.
dc.format.extent Pages: (177-196)
dc.language English
dc.publisher DORDRECHT
dc.relation.ispartof Publication Name: Wireless Networks; Publication Year: 2014; Volume: 20; no. 2; Pages: (177-196);
dc.source Scopus
dc.title An energy efficient Genetic Algorithm based approach for sensor-to-sink binding in multi-sink wireless sensor networks
dc.type Article
dc.contributor.affiliation Safa, H., Department of Computer Science, American University of Beirut, Beirut, Lebanon
dc.contributor.affiliation Moussa, M., Department of Computer Science, American University of Beirut, Beirut, Lebanon
dc.contributor.affiliation Artail, H., Department of Computer and Communication Engineering, American University of Beirut, Beirut, Lebanon
dc.contributor.authorAddress Safa, H.; Department of Computer Science, American University of Beirut, Beirut, Lebanon; email:
dc.contributor.authorCorporate University: American University of Beirut; Faculty: Faculty of Engineering and Architecture; Department: Electrical and Computer Engineering;
dc.contributor.authorDepartment Electrical and Computer Engineering
dc.contributor.authorFaculty Faculty of Engineering and Architecture
dc.contributor.authorInitials Safa, H
dc.contributor.authorInitials Moussa, M
dc.contributor.authorInitials Artail, H
dc.contributor.authorReprintAddress Safa, H (reprint author), Amer Univ Beirut, Dept Comp Sci, Beirut, Lebanon.
dc.contributor.authorUniversity American University of Beirut
dc.description.cited Akyildiz I. F., 2010, WIRELESS SENSOR NETW; Andel TR, 2006, COMPUTER, V39, P48, DOI 10.1109-MC.2006.242; English J, 2006, 2006 23rd Biennial Symposium on Communications, P320, DOI 10.1109-BSC.2006.1644632; Gupta G., 2003, P IEEE INT C COMM IC, V3, P1848; Hasancebi O, 2000, COMPUT STRUCT, V78, P435, DOI 10.1016-S0045-7949(00)00089-4; Kulik J, 2002, WIREL NETW, V8, P169, DOI 10.1023-A:1013715909417; Kim H, 2005, LECT NOTES COMPUT SC, V3391, P264; KIRKPATRICK S, 1983, SCIENCE, V220, P671, DOI 10.1126-science.220.4598.671; Min R., 2000, IEEE WORKSH SIGN PRO, P581; Perkins C. E., 1999, P 2 IEEE WORKSH MOB, V6, P90; Safa H., 2012, P IEEE INT IN PRESS; Safa H., 2011, 2011 Proceedings of IEEE Symposium on Wireless Technology and Applications (ISWTA 2011), DOI 10.1109-ISWTA.2011.6089389; Sinha A., 2000, P 13 INT C VLSI DES, P50; SRINIVAS M, 1994, COMPUTER, V27, P17, DOI 10.1109-2.294849; Tas N. C., 2008, P 17 IEEE INT C COMP, P1; Wang RL, 2004, NEUROCOMPUTING, V57, P463, DOI 10.1016-j.neucom.2003.12.003; Weng C.-E., 2012, COMMUNICATION, DOI [10.1007-s11277-012-0571-0, DOI 10.1007-S11277-012-0571-0]; Yi Poe W, 2008, P 14 GI ITG C MEAS M, P253; Zhu YH, 2011, MOBILE NETW APPL, V16, P58, DOI 10.1007-s11036-009-0211-4
dc.description.citedTotWOSCount 1
dc.description.citedWOSCount 1
dc.format.extentCount 20
dc.identifier.coden WINEF
dc.identifier.scopusID 84892983333
dc.relation.ispartOfISOAbbr Wirel. Netw.
dc.relation.ispartOfIssue 2
dc.relation.ispartofPubTitle Wireless Networks
dc.relation.ispartofPubTitleAbbr Wireless Networks
dc.relation.ispartOfVolume 20
dc.source.ID WOS:000329369700001
dc.type.publication Journal
dc.subject.otherAuthKeyword Genetic Algorithms
dc.subject.otherAuthKeyword Load balancing
dc.subject.otherAuthKeyword Sensor-to-sink binding
dc.subject.otherAuthKeyword Sensors
dc.subject.otherAuthKeyword Sinks
dc.subject.otherIndex Battery replacements
dc.subject.otherIndex Communication distance
dc.subject.otherIndex Limited energies
dc.subject.otherIndex Network simulator NS-2
dc.subject.otherIndex Remaining energies
dc.subject.otherIndex Sensor-to-sink binding
dc.subject.otherIndex Sinks
dc.subject.otherIndex Wireless sensor network (WSNs)
dc.subject.otherIndex Binding energy
dc.subject.otherIndex Energy efficiency
dc.subject.otherIndex Energy utilization
dc.subject.otherIndex Genetic algorithms
dc.subject.otherIndex Resource allocation
dc.subject.otherIndex Sensor nodes
dc.subject.otherIndex Sensors
dc.subject.otherWOS Computer Science, Information Systems
dc.subject.otherWOS Engineering, Electrical and Electronic
dc.subject.otherWOS Telecommunications

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