Michael Stein, Dominic Lerbs, M. Hassan, M. Schnee, Immanuel Schweizer, K. Weihe, M. Mühlhäuser
{"title":"Evaluation study for clustering in wireless sensor networks","authors":"Michael Stein, Dominic Lerbs, M. Hassan, M. Schnee, Immanuel Schweizer, K. Weihe, M. Mühlhäuser","doi":"10.1109/CSNDSP.2016.7573997","DOIUrl":null,"url":null,"abstract":"Typically, wireless sensor nodes are battery-powered. The network's lifetime depends on the energy consumption of the sensor nodes. Transmitting messages causes a good portion of this energy consumption. Clustering the sensor nodes may reduce energy consumption through local communication and aggregation. Many clustering algorithms exist, but corresponding simulation results are hardly comparable. This paper conducts an extensive simulation study. We compare five popular clustering algorithms in four different scenarios under strictly uniform conditions. Our results indicate that two criteria for clustering algorithms are particularly important: considering residual energy for cluster head selection, and small communication overhead during cluster formation.","PeriodicalId":298711,"journal":{"name":"2016 10th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 10th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSNDSP.2016.7573997","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Typically, wireless sensor nodes are battery-powered. The network's lifetime depends on the energy consumption of the sensor nodes. Transmitting messages causes a good portion of this energy consumption. Clustering the sensor nodes may reduce energy consumption through local communication and aggregation. Many clustering algorithms exist, but corresponding simulation results are hardly comparable. This paper conducts an extensive simulation study. We compare five popular clustering algorithms in four different scenarios under strictly uniform conditions. Our results indicate that two criteria for clustering algorithms are particularly important: considering residual energy for cluster head selection, and small communication overhead during cluster formation.