Increasing energy efficiency in wireless sensor networks using GA-ANFIS to choose a cluster head and Assess Routing and Weighted Trusts to demodulate attacker nodes

Basit Öğe Kaydı
dc.contributor.authorAl Hayali, Shaymaa
dc.contributor.authorRahebi, Javad
dc.contributor.authorUçan, Osman Nuri
dc.contributor.authorBayat, Oğuz
dc.date.accessioned2021-05-15T11:33:23Z
dc.date.available2021-05-15T11:33:23Z
dc.date.issued2020
dc.departmentMühendislik ve Doğa Bilimleri Fakültesi, Elektrik - Elektronik Mühendisliği Bölümüen_US
dc.description.abstractDemodulating harmful nodes and diminishing the energy waste in sensor nodes can prolong the lifespan of wireless sensor networks (WSNs). In this study, a genetic algorithm (GA) and an adaptive neuro fuzzy inference system were used to diminish the energy waste of sensors. Weighted trust evaluation was applied to search for harmful nodes in the network to prolong the lifespan of WSNs. A low-energy adaptive clustering hierarchy method was used to analyze the results. It was discovered that searching for harmful nodes with GA-ANFIS using weighted trust evaluation significantly increased the lifespan of WSNs. For evaluation of the proposed method we used the mean of energy of all sensors against of the round, data packets received in base station, minimum energy versus rounds and number of alive sensors versus rounds. Also, in this paper we compared the proposed method results with LEACH, LEACH-DT, Random, SIF and GA-Fuzzy methods. As results the proposed method has high life time than other methods. A representation of the overall system was implemented using MATLAB software.en_US
dc.identifier.doi10.1007/s10699-019-09593-9
dc.identifier.endpage1246en_US
dc.identifier.issn1233-1821
dc.identifier.issn1572-8471
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85062692151
dc.identifier.scopusqualityQ1
dc.identifier.startpage1227en_US
dc.identifier.urihttps://doi.org/10.1007/s10699-019-09593-9
dc.identifier.urihttps://hdl.handle.net/20.500.12939/147
dc.identifier.volume25en_US
dc.identifier.wosWOS:000590044200017
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorBayat, Oğuz
dc.institutionauthorUçan, Osman Nuri
dc.institutionauthorAl Hayali, Shaymaa
dc.language.isoen
dc.publisherSpringeren_US
dc.relation.ispartofFoundations of Science
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectWireless Sensor Networken_US
dc.subjectGenetic Algorithmen_US
dc.subjectAdaptive Neuro-Fuzzy Inference Systemen_US
dc.subjectFuzzyen_US
dc.subjectLEACHen_US
dc.titleIncreasing energy efficiency in wireless sensor networks using GA-ANFIS to choose a cluster head and Assess Routing and Weighted Trusts to demodulate attacker nodes
dc.typeArticle

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Elektrik - Elektronik Mühendisliği Bölümü Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu