Optimal Model for Energy-Efficient Clustering in Wireless Sensor Networks Using Global Simulated Annealing Genetic Algorithm
Jianming Zhang, Yaping Lin, Cuihong Zhou, Jingcheng Ouyang · 2008
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.