Energy efficient self organising load balanced clustering scheme for heterogeneous WSN

Abstract

Clustering is one of the efficient techniques which not only help in protraction of lifetime of wireless sensor network but also make it scalable and robust. Subdivision of network into group of sensor nodes with a coordinator is called a cluster. Cluster members collect the physical data by sensing the environment and forward it to the coordinator which is generally termed as Cluster Head (CH). This cluster head aggregates the data and transmit it to the Base Station for further processing of data to meet the requirement of the application. In this paper we have proposed a novel self organising clustering scheme which considers the real time parameters for setting up the clusters for data collection. Unlike several proposed algorithm, this scheme reclusters the network only when CH fall below a threshold level. Repeated unnecessary clustering in every round depletes the energy of the network more quickly. We have introduced heterogeneity in the proposed work. By virtue of heterogeneity in terms of energy, lifetime of the network can be extended. An algorithm is functional if the area of interest is covered by active nodes. The period for which the network is functional is termed as persistent period in our paper. Simulation results show that the proposed scheme is comparatively more energy efficient, scalable & robust and has longer persistent period.