Show simple item record

dc.contributor.authorZhang, S
dc.contributor.authorLiu, X
dc.contributor.authorWang, J
dc.contributor.authorCao, J
dc.contributor.authorMin, G
dc.date.accessioned2016-03-24T14:49:57Z
dc.date.issued2015-05-01
dc.description.abstractPosition information plays a pivotal role in wireless sensor network (WSN) applications and protocol/ algorithm design. In recent years, range-free localization algorithms have drawn much research attention due to their low cost and applicability to large-scale WSNs. However, the application of range-free localization algorithms is restricted because of their dramatic accuracy degradation in practical anisotropic WSNs, which is mainly caused by large error of distance estimation. Distance estimation in the existing range-free algorithms usually relies on a unified per hop length (PHL) metric between nodes. But the PHL between different nodes might be greatly different in anisotropic WSNs, resulting in large error in distance estimation. We find that, although the PHL between different nodes might be greatly different, it exhibits significant locality; that is, nearby nodes share a similar PHL to anchors that know their positions in advance. Based on the locality of the PHL, a novel distance estimation approach is proposed in this article. Theoretical analyses show that the error of distance estimation in the proposed approach is only one-fourth of that in the state-of-the-art pattern-driven scheme (PDS). An anchor selection algorithm is also devised to further improve localization accuracy by mitigating the negative effects from the anchors that are poorly distributed in geometry. By combining the locality-based distance estimation and the anchor selection, a range-free localization algorithm named Selective Multilateration (SM) is proposed. Simulation results demonstrate that SM achieves localization accuracy higher than 0.3r, where r is the communication radius of nodes. Compared to the state-of-the-art solution, SM improves the distance estimation accuracy by up to 57% and improves localization accuracy by up to 52% consequently.en_GB
dc.description.sponsorshipThis work is partially supported by the National Science Foundation of China (61103203, 61173169, 61332004, and 61420106009), the Hong Kong RGC General Research Fund (PolyU 5106/11E), the International Science & Technology Cooperation Program of China (2013DFB10070), and the EU FP7 QUICK project (PIRSES-GA-2013-612652).en_GB
dc.identifier.citationVol. 11, Iss. 3, Art. No. 51en_GB
dc.identifier.doi10.1145/2746343
dc.identifier.urihttp://hdl.handle.net/10871/20835
dc.language.isoenen_GB
dc.publisherAssociation for Computing Machinery (ACM)en_GB
dc.rightsThis is the author accepted manuscript. The final version is available from Association for Computing Machinery via the DOI in this record.en_GB
dc.subjectWireless sensor networksen_GB
dc.subjectanisotropic wireless networksen_GB
dc.subjectlocalizationen_GB
dc.subjectrange-freeen_GB
dc.subjectanchor selectionen_GB
dc.titleAccurate range-free localization for anisotropic wireless sensor networksen_GB
dc.typeArticleen_GB
dc.date.available2016-03-24T14:49:57Z
dc.identifier.issn1550-4859
dc.descriptionJournal Articleen_GB
dc.identifier.eissn1550-4867
dc.identifier.journalACM Transactions on Sensor Networksen_GB


Files in this item

This item appears in the following Collection(s)

Show simple item record