ENERGY EFFICIENT CLUSTERING IN WIRELESS SENSOR NETWORKS

Abstract

Wireless sensor networks (WSNs) are comprised of hundreds to thousands of tiny battery powered sensor nodes constrained in energy and computation power. Because of limited energy source, economic utilization of energy is a critical issue in wireless sensor networks. Clustering techniques are most often used to reduce the consumption of energy by the sensor nodes due to data transmission. Partitioning the network into optimal number of clusters and selecting an optimal set of nodes as cluster heads is an NP-Hard problem. A widely used class of clustering techniques is probabilistic clustering in which a predetermined optimal probability is used to facilitate the cluster head selection process. In this work, we devised a new technique that improves the energy efficiency of existing probabilistic clustering algorithms by optimizing the number of clusters and the distribution of cluster heads in the network. We also presented two generic approaches to integrate our technique into the existing probabilistic clustering techniques. The simulation results show a considerable improvement in energy efficiency of probabilistic clustering protocols and consequently a prolonged network life time. The NP-Hard nature of clustering problem makes it a suitable candidate for the application of evolutionary algorithm and particle swarm optimization (PSO). In this work, we also suggest a PSO based solution to the optimal clustering problem by using residual energy and transmission distance of sensor nodes. Simulation results show a considerable improvement in network lifetime as compared to existing PSO based algorithms and other clustering protocols like LEACH and SEP. We also present a new hybrid Clustering protocol, EEHCP for Multi-level heterogeneous wireless sensor networks. In this protocol, some nodes transmit data directly to base station while some use clustering technique to send data to base station. The proposed protocol Page | v aims to conserve energy by keeping three key design factors into consideration: (1) Finding the optimal distance up to which a node can directly send the data to base station, (2) electing an appropriate node as cluster head and (3) limiting the number of clusters in the network. The simulation results show that EEHCP enhanced the stability period by approximately 75% and almost tripled the throughput when compared to existing protocols like LEACH and SEP.