A Novel Hybrid Energy Efficient Model using Clustering in Wireless Sensor Networks

Abstract

An innovative hybrid approach is presented in this paper aimed at rapid predicting the optimum routing path selection in WSNs using the Lagrangian method and Clustering. The main motive of this work proposed is to maximize the clustering productivity, reduce the congestion in routing system and optimize the energy range in the network. By combining the route prediction through clustering and energy flow estimates in the routing protocol design-based algorithm, this will combine both the objectives of rapid route prediction and energy flow estimation. A Distributional Heterogeneous Pathfinder (DHP) based routing algorithm was used in this optimal clustering system to predict the best routing paths in the network and to optimize network energy consumption. In general, sensor communication in the Internet of Things takes place with tremendous amounts of data transmission and other interactions. The results drawn from simulation shows the higher efficiency and fast route detection with better energy transmission of data through the network.