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Conference Paper: Improving localization in wireless sensor networks with an evolutionary algorithm

TitleImproving localization in wireless sensor networks with an evolutionary algorithm
Authors
Issue Date2006
PublisherIEEE.
Citation
2006 3Rd Ieee Consumer Communications And Networking Conference, Ccnc 2006, 2006, v. 1, p. 137-141 How to Cite?
AbstractWireless sensor networks are highly useful for many location-sensitive applications including environmental monitoring, military applications, disaster management, etc. Localization in wireless sensor networks concerns about the precise estimation of node positions given a relatively small portion as anchor nodes with their absolute positions predetermined. Intrinsically, localization is an unconstrained optimization problem based on various distance/path measures. Most of the existing work focus on increasing the accuracy in position estimation typically by using different heuristic-based or mathematical techniques. On the other hand, there were many complex optimization problems successfully tackled by the nature inspired search algorithms including the ant-based or genetic algorithms. In this paper, we propose to adapt an evolutionary approach, namely a microgenetic algorithm, and integrate as a post-optimizer into some existing localization techniques such as the Ad-hoc Positioning System (APS) to further improve their position estimation. Clearly, our proposed MGA is so adaptable that it can easily be integrated into other localization methods. More importantly, the remarkable improvements obtained by the prototype of our proposed evolutionary optimizer on certain anisotropic topologies of our simulation tests prompt for further investigation. © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/45880
References

 

DC FieldValueLanguage
dc.contributor.authorTam, Ven_HK
dc.contributor.authorCheng, KYen_HK
dc.contributor.authorLui, KSen_HK
dc.date.accessioned2007-10-30T06:37:37Z-
dc.date.available2007-10-30T06:37:37Z-
dc.date.issued2006en_HK
dc.identifier.citation2006 3Rd Ieee Consumer Communications And Networking Conference, Ccnc 2006, 2006, v. 1, p. 137-141en_HK
dc.identifier.urihttp://hdl.handle.net/10722/45880-
dc.description.abstractWireless sensor networks are highly useful for many location-sensitive applications including environmental monitoring, military applications, disaster management, etc. Localization in wireless sensor networks concerns about the precise estimation of node positions given a relatively small portion as anchor nodes with their absolute positions predetermined. Intrinsically, localization is an unconstrained optimization problem based on various distance/path measures. Most of the existing work focus on increasing the accuracy in position estimation typically by using different heuristic-based or mathematical techniques. On the other hand, there were many complex optimization problems successfully tackled by the nature inspired search algorithms including the ant-based or genetic algorithms. In this paper, we propose to adapt an evolutionary approach, namely a microgenetic algorithm, and integrate as a post-optimizer into some existing localization techniques such as the Ad-hoc Positioning System (APS) to further improve their position estimation. Clearly, our proposed MGA is so adaptable that it can easily be integrated into other localization methods. More importantly, the remarkable improvements obtained by the prototype of our proposed evolutionary optimizer on certain anisotropic topologies of our simulation tests prompt for further investigation. © 2006 IEEE.en_HK
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dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartof2006 3rd IEEE Consumer Communications and Networking Conference, CCNC 2006en_HK
dc.rights©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleImproving localization in wireless sensor networks with an evolutionary algorithmen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailTam, V:vtam@eee.hku.hken_HK
dc.identifier.emailLui, KS:kslui@eee.hku.hken_HK
dc.identifier.authorityTam, V=rp00173en_HK
dc.identifier.authorityLui, KS=rp00188en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/CCNC.2006.1593003en_HK
dc.identifier.scopuseid_2-s2.0-33749068872en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33749068872&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume1en_HK
dc.identifier.spage137en_HK
dc.identifier.epage141en_HK
dc.identifier.scopusauthoridTam, V=7005091988en_HK
dc.identifier.scopusauthoridCheng, KY=14631590500en_HK
dc.identifier.scopusauthoridLui, KS=7103390016en_HK

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