Neural Network Based Energy Efficient Clustering and Routing in Wireless Sensor Networks

Abstract

Energy is a valuable resource in wireless sensor networks (WSNs). The status of energy consumption should be continuously monitored after network deployment. The information about energy status can be used to early notify both sensor nodes and network deployers about resource depletion in some parts of the network. It can also be used to perform energy-efficient routing in WSNs. In this paper, we propose a neural network based clustering and energy efficient routing in WSN with the objective of maximizing the network lifetime. In the proposed scheme, the problem is formulated as linear programming (LP) with specified constraints. Cluster head selection is done using adaptive learning in neural networks followed by routing and data transmission. The simulation results show that the proposed scheme can be used in wide area of applications in WSNs.