A HYBRID APPROACH OF FUZZY C-MEANS CLUSTERING AND NEURAL NETWORK TO MAKE ENERGY-EFFICIENT HETEROGENEOUS WIRELESS SENSOR NETWORK

Abstract

The Wireless sensor network has been exceptionally engaged examination region as of late because of its wide applications and versatility to various conditions. The energy-compelled sensor nodes are consistently getting looked at to expand their lifetime. In this paper, we have utilized the benefits of two methodologies i.e., fluffy c-implies grouping and neural network to make an energy productive network by drawing out the lifetime of the network. The group arrangement is finished utilizing FCM to shape similarly estimated bunches in-network and the choice of picking bunch head is finished utilizing neural network having input factors as distance from the base station, heterogeneity, and energy of the node and so forth Our Approach has effectively expanded the lifetime and information limit of the network and outflanked various methodologies applied to the network present in writing.