Optimal Model for Energy-Efficient Clustering in Wireless Sensor Networks Using Global Simulated Annealing Genetic Algorithm

Since the operations of sensors in wireless sensor networks (WSNs) mainly rely on battery energy, energy consumption becomes an important issue. In this paper, we use a global simulated annealing genetic algorithm (GSAGA) to create energy efficient clusters for routing in WSNs. The simulation result...

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Hauptverfasser:	Jianming Zhang, Yaping Lin, Cuihong Zhou, Jingcheng Ouyang
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Clustering algorithms Computational modeling Educational institutions Energy consumption Energy efficiency Energy management energy-efficient clustering Genetic algorithms global simulated annealing genetic algorithm Protocols Simulated annealing Wireless sensor networks
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Beschreibung
Zusammenfassung:	Since the operations of sensors in wireless sensor networks (WSNs) mainly rely on battery energy, energy consumption becomes an important issue. In this paper, we use a global simulated annealing genetic algorithm (GSAGA) to create energy efficient clusters for routing in WSNs. The simulation results show that the proposed GSAGA algorithm has higher efficiency and can achieve better network lifetime and data delivery at the base station than a few existing cluster-based routing protocols.
DOI:	10.1109/IITA.Workshops.2008.40