Vijayalakshmi Senniappan, J. Subramanian, A. Thirumal
{"title":"Application of novel swarm intelligence algorithm for congestion control in structural health monitoring","authors":"Vijayalakshmi Senniappan, J. Subramanian, A. Thirumal","doi":"10.1109/TENCON.2016.7847951","DOIUrl":null,"url":null,"abstract":"Buildings today are a complex integration of structures, systems and technology. Sensors are increasingly being installed in buildings to gather data about the various factors which helps to monitor the health of the structural components. Energy efficiency and network congestion are the most common issues faced by the sensor nodes. The proposed piece of work, uses a bio inspired swarm intelligence algorithm to improve the energy efficiency of the sensor nodes and mitigates congestion by forming clusters. The proposed method employes Biography Based Krill Herd algorithm for improving the network performance. The results of the proposed method, when compared with other classical evolutionary optimizations, has shown an increase of 42.11% of the network lifetime.","PeriodicalId":246458,"journal":{"name":"2016 IEEE Region 10 Conference (TENCON)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Region 10 Conference (TENCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TENCON.2016.7847951","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Buildings today are a complex integration of structures, systems and technology. Sensors are increasingly being installed in buildings to gather data about the various factors which helps to monitor the health of the structural components. Energy efficiency and network congestion are the most common issues faced by the sensor nodes. The proposed piece of work, uses a bio inspired swarm intelligence algorithm to improve the energy efficiency of the sensor nodes and mitigates congestion by forming clusters. The proposed method employes Biography Based Krill Herd algorithm for improving the network performance. The results of the proposed method, when compared with other classical evolutionary optimizations, has shown an increase of 42.11% of the network lifetime.
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