Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/334230
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dc.coverage.spatialCertain investigations on improving lifetime of wireless sensor networks through hybrid optimization techniques
dc.date.accessioned2021-08-02T04:34:28Z-
dc.date.available2021-08-02T04:34:28Z-
dc.identifier.urihttp://hdl.handle.net/10603/334230-
dc.description.abstractWireless Sensor Networks (WSNs) consist of a number of nodes that transfer data to the sink nodes through the Cluster Heads (CHs). Each node acts as a sensor and the data are transferred using a particular cluster termed as CH. The data are transferred to the sink node only when the sink node is present within the transmission range, but if the sink is present at a longer distance from the source, then routing process takes place with the neighbouring nodes or clusters that are directly connected to the sink or with the selection of any one of CHs to transmit the data. This process is carried out until the data are received by the sink node. Data clustering in WSN is a major research area that ensures efficient communication to satisfy energy constraints. The existing routing protocols concentrate on data collection from different environments using WSNs. They must forward the data to control station with minimal delay and enhanced lifetime of the network. In the present research, a hybrid optimization algorithm is proposed to handle the CH selection efficiently in order to ensure energyaware routing and effective communication in WSNs. The optimization algorithm, called Dolphin Echolocation-based Crow Search Algorithm (DECSA) is the combination of Crow Search Algorithm (CSA) and Dolphin Echolocation (DE) algorithm. It provides hybrid optimization of energy conservation for the selection of CHs based on the multi constraints effectively and with high convergence rate. The energy-aware efficient routing is implemented in WSN using the proposed algorithm. The performance metrics of the clustering algorithm are compared through simulation obtained in WSN environment using 50, 75, and 100 nodes newline
dc.format.extentxxvi,119p.
dc.languageEnglish
dc.relationp.111-118
dc.rightsuniversity
dc.titleCertain investigations on improving lifetime of wireless sensor networks through hybrid optimization techniques
dc.title.alternative
dc.creator.researcherMahesh, N
dc.subject.keywordWireless sensor networks
dc.subject.keywordHybrid optimization
dc.subject.keywordCluster Heads
dc.description.note
dc.contributor.guideVijayachitra, S
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2020
dc.date.awarded2020
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File30.65 kBAdobe PDFView/Open
02_certificates.pdf282.97 kBAdobe PDFView/Open
03_vivaproceedings.pdf472.19 kBAdobe PDFView/Open
04_bonafidecertificate.pdf342.01 kBAdobe PDFView/Open
05_abstracts.pdf10.05 kBAdobe PDFView/Open
06_acknowledgements.pdf441.18 kBAdobe PDFView/Open
07_contents.pdf23.08 kBAdobe PDFView/Open
08_listoftables.pdf6.46 kBAdobe PDFView/Open
09_listoffigures.pdf11.88 kBAdobe PDFView/Open
10_listofabbreviations.pdf181.16 kBAdobe PDFView/Open
11_chapter1.pdf254.59 kBAdobe PDFView/Open
12_chapter2.pdf31.21 kBAdobe PDFView/Open
13_chapter3.pdf666.71 kBAdobe PDFView/Open
14_chapter4.pdf425.76 kBAdobe PDFView/Open
15_chapter5.pdf665.01 kBAdobe PDFView/Open
16_chapter6.pdf11.94 kBAdobe PDFView/Open
17_conclusion.pdf11.94 kBAdobe PDFView/Open
18_references.pdf36.05 kBAdobe PDFView/Open
19_listofpublications.pdf5.12 kBAdobe PDFView/Open
80_recommendation.pdf57.26 kBAdobe PDFView/Open


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