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The Optimization of Network Lifetime With Sensor Deployment for Target Coverage Problem in Wireless Sensor Networks

dc.authorid Ozdag, Recep/0000-0001-5247-5591
dc.authorscopusid 7801614799
dc.contributor.author Özdaǧ, R.
dc.date.accessioned 2025-05-10T17:01:08Z
dc.date.available 2025-05-10T17:01:08Z
dc.date.issued 2017
dc.department T.C. Van Yüzüncü Yıl Üniversitesi en_US
dc.department-temp Özdaǧ R., Yözöncö Yil Üniversitesi, Möhendislik Faköltesi, Bilgisayar Möhendisliǧi Bölömö, Van, 65080, Turkey en_US
dc.description.abstract Network lifetime is a critical factor in determining the effectiveness of Wireless Sensor Networks (WSNs). The optimization of the battery lives of the sensor nodes following the targets in terms of continuity of WSNs coverage in military and civil applications plays an important role in extending the network's lifetime. Since the sensor nodes that constitute WSNs have limited battery life, the energy of the sensors gradually decreases as a result of communicating among themselves and perceiving field of interest. Ultimately, the node consumes its energy completely and causes WSN to fail to function. For this reason, the optimization of the lifetime of WSNs has been one of the most frequently studied topics in the literature.In this article, it was aimed to optimize the lifetime of the network by performing dynamic distributions of the nodes provided that the coverage requirements (1 ≤ k ≤ 4) of the maximum four sensor nodes are met to find solution to the target coverage problem in WSNs. It was aimed to determine the accessible lifetime of the network by calculating the remaining battery life of the nodes and the upper limit of the network lifetime when the coverage requirements of the targets are met. In addition, Electromagnetism-Like (EM) algorithm, which is meta-heuristic in performing the dynamic distributions of sensor nodes, was taken as a basis, and a new energy-efficient algorithm was developed. The accessible network lifetimes calculated with this algorithm were compared with the Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) algorithms in the literature. According to the obtained simulation results, it was found that the algorithm developed in reaching the upper limit of the network lifetime gave more optimum results. en_US
dc.description.woscitationindex Science Citation Index Expanded
dc.identifier.doi 10.17341/gazimmfd.369516
dc.identifier.endpage 1167 en_US
dc.identifier.issn 1300-1884
dc.identifier.issue 4 en_US
dc.identifier.scopus 2-s2.0-85038818111
dc.identifier.scopusquality Q3
dc.identifier.startpage 1155 en_US
dc.identifier.uri https://doi.org/10.17341/gazimmfd.369516
dc.identifier.uri https://hdl.handle.net/20.500.14720/5066
dc.identifier.volume 32 en_US
dc.identifier.wos WOS:000417994200013
dc.identifier.wosquality Q4
dc.institutionauthor Özdaǧ, R.
dc.language.iso tr en_US
dc.publisher Gazi Universitesi Muhendislik-Mimarlik en_US
dc.relation.ispartof Journal of the Faculty of Engineering and Architecture of Gazi University en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject K-Coverage Requirement en_US
dc.subject Network Lifetime en_US
dc.subject Sensor Deployment en_US
dc.subject Target Coverage Problem en_US
dc.subject Wireless Sensor Networks en_US
dc.title The Optimization of Network Lifetime With Sensor Deployment for Target Coverage Problem in Wireless Sensor Networks en_US
dc.type Article en_US

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