WSN Cluster Head Selection Algorithm Based on Neural Network
Lejiang Guo, Fangxin Chen, Zhicheng Dai, Zhuo Liu · 2010
As an effective way to control the network topology, the clustering algorithm can significantly reduce the energy consumption of wireless sensor networks and improve network throughput. Through learning the framework of clustering algorithm for wireless sensor networks, this paper presents a weighted average of cluster head selection algorithm based on BP neural network which make node weights directly related to the decision-making predictions. The weight distribution of nodes is objective. The simulation results show that efficiency of the algorithm in eliminating data redundancy, reducing network traffic, extending the network lifetime.