Energy Efficient Sleep Scheduled Clustering & Spanning Tree based data aggregation in wireless sensor network

Wireless sensor networks (WSNs) are mainly used for systematic gathering of useful information and for the transmission of the gathered data to the base station for further processing. Despite the innumerable applications of WSNs, the sensor nodes of these networks have limited energy, limited computing power and limited bandwidth, in which energy is major constraint. Clustering has been widely used in WSNs to reduce energy consumption, which decrease the communication load, and thereby prolong the network lifetime by minimizing the redundant information using the data aggregation model on the cluster heads. In this paper, we have proposed an information similarity based clustering algorithm where transmission of the data to the sink is done using the least spanning tree algorithm. This approach firstly uses improved LEACH algorithm for election of cluster heads and then cluster formation under the elected cluster heads is done depending upon the non-cluster head node's maximum information similarity with the cluster head nodes. By utilizing the sleep scheduling & least spanning tree algorithm, this approach effectively reduces the redundant data transmission and whole energy consumed in the network. Simulation results show that network lifetime has increased effectively in comparison to other clustering algorithm such as LEACH.