Improving Energy Efficiency Wireless Sensor Networks Clustering Based on SVM

A wireless sensor Network (WSN) is organized of multiple nodes in a large area distributed randomly, each node was sending information at same time that led to conflict among them, the goal is to resolve the emerging complex conflict in WSN through the utilization of Procedure for electing the own cluster. This required need to optimize the own cluster election and extending life cycle of network. In this paper a support vector machine (SVM) based on clustering algorithm is proposed during election process. The WSN has remaining energy of node, distance from base station and probability of node serving as own cluster. The own cluster is optimized by SVM algorithm to adaptive inertia weight, it considers nodes within the communication range are regarded as its cluster members such number of own clusters selected to satisfies the optimal number of own clusters, and thereby further improving energy efficiency of the network. The simulation results show that the SVM algorithm is more efficient when compared to other algorithms, also the algorithm proven that period of network stability in balancing consuming energy is more effective and more extending the network life cycle.