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Cited 18 time in webofscience Cited 21 time in scopus
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A Cluster Based Localization Scheme with Partition Handling for Mobile Underwater Acoustic Sensor Networks

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dc.contributor.authorIslam, Tariq-
dc.contributor.authorLee, Yong Kyu-
dc.date.accessioned2023-04-28T04:42:11Z-
dc.date.available2023-04-28T04:42:11Z-
dc.date.issued2019-03-01-
dc.identifier.issn1424-8220-
dc.identifier.issn1424-3210-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/8306-
dc.description.abstractMany applications of underwater sensor networks (UWSNs), such as target tracking, reconnaissance and surveillance, and marine life monitoring require information about the geographic locations of the sensed data. This makes the localization of sensor nodes a crucial part of such underwater sensing missions. In the case of mobile UWSNs, the problem becomes challenging, not only due to a need for the periodic tracking of nodes, but also due to network partitioning as a result of the pseudo-random mobility of nodes. In this work, we propose an energy efficient solution for localizing nodes in partitioned networks. Energy consumption is minimized by clustering unlocalized partitioned nodes and allowing only clusterheads to carry out a major part of the localization procedure on behalf of the whole cluster. Moreover, we introduce a retransmission control scheme that reduces energy consumption by controlling unnecessary transmission. The major design goal of our work is to maximize localization coverage while keeping communication overheads at a minimum, thus achieving better energy efficiency. The major contributions of this paper include a clustering technique for localizing partitioned nodes and a retransmission control strategy that reduces unnecessary transmissions.-
dc.language영어-
dc.language.isoENG-
dc.publisherMDPI-
dc.titleA Cluster Based Localization Scheme with Partition Handling for Mobile Underwater Acoustic Sensor Networks-
dc.typeArticle-
dc.publisher.location스위스-
dc.identifier.doi10.3390/s19051039-
dc.identifier.scopusid2-s2.0-85062433933-
dc.identifier.wosid000462540400058-
dc.identifier.bibliographicCitationSENSORS, v.19, no.5-
dc.citation.titleSENSORS-
dc.citation.volume19-
dc.citation.number5-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaChemistry-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaInstruments & Instrumentation-
dc.relation.journalWebOfScienceCategoryChemistry, Analytical-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryInstruments & Instrumentation-
dc.subject.keywordAuthorunderwater acoustic sensor networks-
dc.subject.keywordAuthorlocalization-
dc.subject.keywordAuthormobility-
dc.subject.keywordAuthorGPS-
dc.subject.keywordAuthorclustering-
dc.subject.keywordAuthordata-tagging-
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College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 1. Journal Articles

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