Lifetime maximization considering target coverage and connectivity in directional image/video sensor networks
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Yong-hwan | - |
dc.contributor.author | Han, Youn-Hee | - |
dc.contributor.author | Jeong, Young-Sik | - |
dc.contributor.author | Park, Doo-Soon | - |
dc.date.accessioned | 2021-08-12T01:13:34Z | - |
dc.date.available | 2021-08-12T01:13:34Z | - |
dc.date.issued | 2013-07 | - |
dc.identifier.issn | 0920-8542 | - |
dc.identifier.issn | 1573-0484 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/13568 | - |
dc.description.abstract | A directional sensor network consists of a large number of directional sensors (e.g., image/video sensors), which have a limited angle of sensing range due to technical constraints or cost considerations. In such directional sensor networks, the power saving issue is a challenging problem. In this paper, we address the Directional Cover and Transmission (DCT) problem of organizing the directional sensors into a group of non-disjoint subsets to extend the network lifetime. One subset in which the directional sensors cover all the targets and forward the sensed data to the sink is activated at one time, while the others sleep to conserve their energy. For the DCT problem proven to be the NP-complete problem, we present a heuristic algorithm called the Shortest Path from Target to Sink (SPTS)-greedy algorithm. To verify and evaluate the proposed algorithm, we conduct extensive simulations and show that it can contribute to extending the network lifetime to a reasonable extent. | - |
dc.format.extent | 18 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Kluwer Academic Publishers | - |
dc.title | Lifetime maximization considering target coverage and connectivity in directional image/video sensor networks | - |
dc.type | Article | - |
dc.publisher.location | 네델란드 | - |
dc.identifier.doi | 10.1007/s11227-011-0646-9 | - |
dc.identifier.scopusid | 2-s2.0-84878833265 | - |
dc.identifier.wosid | 000319942000023 | - |
dc.identifier.bibliographicCitation | Journal of Supercomputing, v.65, no.1, pp 365 - 382 | - |
dc.citation.title | Journal of Supercomputing | - |
dc.citation.volume | 65 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 365 | - |
dc.citation.endPage | 382 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | sci | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Hardware & Architecture | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordPlus | TRACKING | - |
dc.subject.keywordAuthor | Directional sensor networks | - |
dc.subject.keywordAuthor | Scheduling | - |
dc.subject.keywordAuthor | Target coverage | - |
dc.subject.keywordAuthor | Connectivity | - |
dc.subject.keywordAuthor | Energy efficiency | - |
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