Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/7403
Full metadata record
DC FieldValueLanguage
dc.contributor.authorRaval, Gaurang-
dc.contributor.authorBhavsar, Madhuri-
dc.date.accessioned2017-02-16T08:47:57Z-
dc.date.available2017-02-16T08:47:57Z-
dc.date.issued2015-03-
dc.identifier.issn0975 – 8887-
dc.identifier.urihttp://hdl.handle.net/123456789/7403-
dc.descriptionInternational Journal of Computer Applications Vol. 113 (19), March, 2015, Page No.41 - 47en_US
dc.description.abstractIn this paper an energy usage estimation technique (LCEFCM) has been proposed which employs the Fuzzy C-Means clustering for creating clusters in the Wireless Sensor Networks. LCEFCM reduces the energy consumption considerably compared to other clustering methods like simulated annealing and K-Means clustering. It applies the dynamic clustering mechanism combined with balanced clustering method. LCEFCM outperforms LEACHC, LEACHC Estimate(LCE) and LCEKMeans for various performance measuring factors like network lifetime, data received, alive nodes etc.en_US
dc.relation.ispartofseriesITFIT002-12;-
dc.subjectWSNen_US
dc.subjectEnergy Estimationen_US
dc.subjectThresholden_US
dc.subjectFCMen_US
dc.subjectComputer Faculty Paperen_US
dc.subjectFaculty Paperen_US
dc.subjectITFIT002en_US
dc.subjectITFIT004en_US
dc.titleImproving Energy Estimation based Clustering with Energy Threshold for Wireless Sensor Networksen_US
dc.typeFaculty Papersen_US
Appears in Collections:Faculty Papers, CE

Files in This Item:
File Description SizeFormat 
ITFIT002-12.pdfITFIT002-12360.42 kBAdobe PDFThumbnail
View/Open


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