Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/1781
Full metadata record
DC FieldValueLanguage
dc.contributor.authorP. Subramanian
dc.contributor.authorJ. Martin Sahayaraj
dc.contributor.authorS. Senthilkumar
dc.contributor.authorD. Stalin Alex
dc.date.accessioned2022-05-23T08:44:19Z-
dc.date.available2022-05-23T08:44:19Z-
dc.date.issued2020
dc.identifier.citationWireless Personal Communications
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/1781-
dc.description.abstractClustering is considered as one of the most primitive technique that aids in prolonging the lifetime expectancy of wireless sensor networks (WSNs). But, the process of cluster head selection concerning energy stabilization for the purposed of prolonging the network life expectancy still remains a major issue in WSNs. In this paper, a hybrid grey wolf and crow search optimization algorithm-based optimal cluster head selection (HGWCSOA-OCHS) scheme was proposed for enhancing the lifetime expectancy of the network by concentrating on the minimization of delay, minimization of distance between nodes and energy stabilization. The grey wolf optimization algorithm is hybridized with the crow search optimization algorithm for resolving the issue of premature convergence that prevents it from exploring the search space in an effective manner. This hybridization of GWO and CSO algorithm in the process of cluster head selection maintains the tradeoff between the exploitation and exploration degree in the search space. The simulation experiments are conducted and the results of the proposed HGWCSOA-OCHS scheme is compared with the benchmarked cluster head selection schemes with firefly optimization (FFO), artificial bee colony optimization (ABCO), grey wolf optimization (GWO), firefly cyclic grey wolf optimisation (FCGWO). The proposed HGWCSOA-OCHS scheme confirmed minimized energy consumption, improved network lifetime expectancy by balancing the percentage of alive and dead sensor nodes in the network.
dc.format.extent9
dc.language.isoen
dc.publisherSpringer
dc.titleA Hybrid Grey Wolf and Crow Search Optimization Algorithm-Based Optimal Cluster Head Selection Scheme for Wireless Sensor Networks
dc.typeArticle
Appears in Collections:Computer Science Engineering Department

Files in This Item:
File SizeFormat 
CSE-33.docx16.44 kBMicrosoft Word XMLView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.