A Probability-Based Clustering Algorithm with CH Election for Expanding WSN Life Span
Clustering achieves energy efficiency and scalable performance in wireless sensor networks (WSNs). A cluster is formed by several sensors nodes, and one of them is elected as Cluster-head (CH). A CH collects information from the cluster members and sends aggregated data to the base station or anothe...
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          | Published in | International journal of electronics, communications, and measurement engineering Vol. 9; no. 1; pp. 1 - 14 | 
|---|---|
| Main Authors | , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        Hershey
          IGI Global
    
        01.01.2020
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| Subjects | |
| Online Access | Get full text | 
| ISSN | 2578-7551 2578-7543  | 
| DOI | 10.4018/IJECME.2020010101 | 
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| Abstract | Clustering achieves energy efficiency and scalable performance in wireless sensor networks (WSNs). A cluster is formed by several sensors nodes, and one of them is elected as Cluster-head (CH). A CH collects information from the cluster members and sends aggregated data to the base station or another CH. This article proposes a new clustering algorithm (EMESISC) that is based on each node's probability of becoming a CH. This node's probability depends on its residual energy, buffer length, and received signal power. We compared EMESISC with LEACH algorithm. Simulation results showed that EMESISC is superior to LEACH. | 
    
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| AbstractList | Clustering achieves energy efficiency and scalable performance in wireless sensor networks (WSNs). A cluster is formed by several sensors nodes, and one of them is elected as Cluster-head (CH). A CH collects information from the cluster members and sends aggregated data to the base station or another CH. This article proposes a new clustering algorithm (EMESISC) that is based on each node's probability of becoming a CH. This node's probability depends on its residual energy, buffer length, and received signal power. We compared EMESISC with LEACH algorithm. Simulation results showed that EMESISC is superior to LEACH. | 
    
| Author | Kanellopoulos, Dimitris N Gite, Pratik  | 
    
| AuthorAffiliation | Institute of Engineering and Sciences, IES-IPS Academy, Indore, India University of Patras, Patras, Greece  | 
    
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| References | G.Popovic (IJECME.2020010101-20) 2016; 1 IJECME.2020010101-11 IJECME.2020010101-10 IJECME.2020010101-15 IJECME.2020010101-14 IJECME.2020010101-13 IJECME.2020010101-12 IJECME.2020010101-19 IJECME.2020010101-18 IJECME.2020010101-17 IJECME.2020010101-16 J.Zander (IJECME.2020010101-28) 2016 IJECME.2020010101-3 IJECME.2020010101-5 IJECME.2020010101-6 IJECME.2020010101-0 IJECME.2020010101-1 IJECME.2020010101-2 W.Seah (IJECME.2020010101-22) 2010 IJECME.2020010101-7 IJECME.2020010101-21 IJECME.2020010101-9 D.Dembla (IJECME.2020010101-4) 2013; 4 IJECME.2020010101-26 IJECME.2020010101-25 IJECME.2020010101-24 IJECME.2020010101-23 Y.Feng (IJECME.2020010101-8) 2013; 7 IJECME.2020010101-27  | 
    
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| SubjectTerms | Algorithms Clustering Communication Energy consumption Energy efficiency Engineering Fault tolerance Load Optimization techniques Residual energy Sensors Wireless sensor networks  | 
    
| Title | A Probability-Based Clustering Algorithm with CH Election for Expanding WSN Life Span | 
    
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