Ant Colony Optimization Algorithm for Lifetime Maximization in Wireless Sensor Network with Mobile Sink
DC Field | Value | Language |
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dc.contributor.author | Zhong, Jing-hui | - |
dc.contributor.author | Zhang, Jun | - |
dc.date.accessioned | 2023-12-08T10:29:21Z | - |
dc.date.available | 2023-12-08T10:29:21Z | - |
dc.date.issued | 2012-07 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/116115 | - |
dc.description.abstract | In wireless sensor networks (WSNs), sensors near the sink can be burdened with a large amount of traffic, because they have to transmit data generated by themselves and those far away from the sink. Hence the sensors near the sink would deplete their energy much faster than the others, which results in a short network lifetime. Using mobile sink is an effective way to tackle this issue. This paper explores the problem of determining the optimal movements of the mobile sink to maximize the network lifetime. A novel ant colony optimization algorithm (ACO), namely the ACO-MSS, is developed to solve the problem. The proposed ACO-MSS takes advantage of the global search ability of ACO and adopts effective heuristic information to find a near globally optimal solution. Multiple practical factors such as the forbidden regions and the maximum moving distance of the sink are taken into account to facilitate the real applications. The proposed ACO-MSS is validated by a series of simulations on WSNs with different characteristics. The simulation results demonstrate the effectiveness of the proposed algorithms. | - |
dc.format.extent | 6 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | ASSOC COMPUTING MACHINERY | - |
dc.title | Ant Colony Optimization Algorithm for Lifetime Maximization in Wireless Sensor Network with Mobile Sink | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1145/2330163.2330328 | - |
dc.identifier.scopusid | 2-s2.0-84864674646 | - |
dc.identifier.wosid | 000309611100150 | - |
dc.identifier.bibliographicCitation | GECCO '12: Proceedings of the 14th annual conference on Genetic and evolutionary computation, pp 1199 - 1204 | - |
dc.citation.title | GECCO '12: Proceedings of the 14th annual conference on Genetic and evolutionary computation | - |
dc.citation.startPage | 1199 | - |
dc.citation.endPage | 1204 | - |
dc.type.docType | Proceedings Paper | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Mathematical & Computational Biology | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.relation.journalWebOfScienceCategory | Mathematical & Computational Biology | - |
dc.subject.keywordAuthor | Ant colony optimization | - |
dc.subject.keywordAuthor | Lifetime maximization | - |
dc.subject.keywordAuthor | Mobile sink scheduling | - |
dc.subject.keywordAuthor | Wireless sensor network | - |
dc.identifier.url | https://dl.acm.org/doi/10.1145/2330163.2330328 | - |
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