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Conference Paper: Localization in sensor networks with limited number of anchors and clustered placement

TitleLocalization in sensor networks with limited number of anchors and clustered placement
Authors
Issue Date2007
Citation
Ieee Wireless Communications And Networking Conference, Wcnc, 2007, p. 4428-4432 How to Cite?
AbstractMany localization algorithms have been proposed in recent years. Although different algorithms based on different methodologies, the use of anchors is common to most algorithms. The placement and the density of anchors affect the accuracy of different algorithms to different extent. Location estimates are usually more accurate with a higher density of anchors. When there are only a few anchors, efficient algorithms tend to perform poorly. However, having more anchors will increase the cost of a sensor network. In this paper, we present an algorithm which uses two different localization techniques, multidimensional scaling (MDS) and proximity-distance map (PDM), in a phased approach. MDS has a high complexity but can give good results when there are only very few anchors. PDM, on the other hand, is a distributed algorithm but performs poorly when anchors are scarce. The phased approach has comparable complexity to PDM but less than MDS. With extensive simulations, we demonstrate that the proposed algorithm gives accurate solution with very few anchors or clustered anchors which is intrinsically a difficult challenge to most existing algorithms. ©2007 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/99336
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorCheng, KYen_HK
dc.contributor.authorLui, KSen_HK
dc.contributor.authorTam, Ven_HK
dc.date.accessioned2010-09-25T18:25:40Z-
dc.date.available2010-09-25T18:25:40Z-
dc.date.issued2007en_HK
dc.identifier.citationIeee Wireless Communications And Networking Conference, Wcnc, 2007, p. 4428-4432en_HK
dc.identifier.issn1525-3511en_HK
dc.identifier.urihttp://hdl.handle.net/10722/99336-
dc.description.abstractMany localization algorithms have been proposed in recent years. Although different algorithms based on different methodologies, the use of anchors is common to most algorithms. The placement and the density of anchors affect the accuracy of different algorithms to different extent. Location estimates are usually more accurate with a higher density of anchors. When there are only a few anchors, efficient algorithms tend to perform poorly. However, having more anchors will increase the cost of a sensor network. In this paper, we present an algorithm which uses two different localization techniques, multidimensional scaling (MDS) and proximity-distance map (PDM), in a phased approach. MDS has a high complexity but can give good results when there are only very few anchors. PDM, on the other hand, is a distributed algorithm but performs poorly when anchors are scarce. The phased approach has comparable complexity to PDM but less than MDS. With extensive simulations, we demonstrate that the proposed algorithm gives accurate solution with very few anchors or clustered anchors which is intrinsically a difficult challenge to most existing algorithms. ©2007 IEEE.en_HK
dc.languageengen_HK
dc.relation.ispartofIEEE Wireless Communications and Networking Conference, WCNCen_HK
dc.titleLocalization in sensor networks with limited number of anchors and clustered placementen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailLui, KS:kslui@eee.hku.hken_HK
dc.identifier.emailTam, V:vtam@eee.hku.hken_HK
dc.identifier.authorityLui, KS=rp00188en_HK
dc.identifier.authorityTam, V=rp00173en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/WCNC.2007.806en_HK
dc.identifier.scopuseid_2-s2.0-36348943560en_HK
dc.identifier.hkuros125284en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-36348943560&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage4428en_HK
dc.identifier.epage4432en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridCheng, KY=14631590500en_HK
dc.identifier.scopusauthoridLui, KS=7103390016en_HK
dc.identifier.scopusauthoridTam, V=7005091988en_HK
dc.identifier.citeulike3158371-

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