{"title":"Zone based Algorithm for CH Selection using Fuzzy logic for Heterogeneous Wireless Sensor Networks","authors":"Wided Abidi, Djamal Djabour, T. Ezzedine","doi":"10.1109/mms48040.2019.9157287","DOIUrl":null,"url":null,"abstract":"A Wireless sensor network is a collection of sensor nodes which are limited energy resources. Therefore, the main issue is how to optimize the energy consumption to maintain the sensor nodes alive as long as possible. In this paper, we propose a new algorithm that divides the network area to zones and uses the fuzzy logic method to select Cluster Heads (CHs). To this aim, we have taken into account a set of parameters related to the node for selecting CHs. These parameters are used as inputs to the Fuzzy Inference System. Simu-lation results show that our algorithm succeeds to increase the stability period, save the energy and hence, prolong the lifetime of the network.","PeriodicalId":373813,"journal":{"name":"2019 IEEE 19th Mediterranean Microwave Symposium (MMS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 19th Mediterranean Microwave Symposium (MMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/mms48040.2019.9157287","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A Wireless sensor network is a collection of sensor nodes which are limited energy resources. Therefore, the main issue is how to optimize the energy consumption to maintain the sensor nodes alive as long as possible. In this paper, we propose a new algorithm that divides the network area to zones and uses the fuzzy logic method to select Cluster Heads (CHs). To this aim, we have taken into account a set of parameters related to the node for selecting CHs. These parameters are used as inputs to the Fuzzy Inference System. Simu-lation results show that our algorithm succeeds to increase the stability period, save the energy and hence, prolong the lifetime of the network.