Selection of Cluster Head in Wireless Sensor Network using Convolution Neural Network Algorithm

Network lifetime enhancement is one of the primary goals for all the Wireless Sensor Network (WSN) applications. Clustering process helps the WSNs to improve its lifetime by forming a group with nearby sensor nodes. A primary node called cluster head is elected from the group for managing the data transmission from the other clustering groups to the basic sensor nodes. Also, the cluster heads are placed to transfer the signal collected from its sensor nodes to the base stations. Identifying an optimum node for making it as a cluster head is a challengeable process for many WSN applications. The proposed work is employed with a neural network algorithm for electing a cluster head by analyzing the residual energy, base station distance and neighbor sensor counts. The experimental work carried out in the paper indicates a betterment on survival node time and energy consumption.