The Hybrid Compressive Sensing Data Collection Method in Cluster Structure for Efficient Data Transmission in WSN

Wireless sensor network consists of large number of wireless node that are responsible for sensing processing and monitoring environmental. These sensor nodes are battery operated. Clustering is a standard approach for achieving efficient and scalable performance in WSN. Compressive sensing (CS) reduces the amount of data transmission and balances the load of traffic throughout the network. In WSN the total number of transmission for collection of data using pure CS is large. Therefore we are using the hybrid CS method to reduce the number of transmission in sensor network. Though the previous work uses the CS on routing trees method. In this paper, we propose a clustering method that uses hybrid CS for WSN. Clusters are formed by group of sensor nodes where each sensor node in cluster sends their data to cluster head (CH) without using CS, further using CS each CH transmits their data to sink. An analytical model shows the relationship between the number of transmission and cluster size in hybrid CS method. We define a new cost function, with the objective of simultaneously minimizing the intra-cluster distance and optimizing the energy consumption of the network. Obtaining the results from analytical model a centralized clustering algorithm is being proposed. Further a distributed implementation of clustering method is presented. Finally our new approach of energy optimization, shows the amount of energy optimized during data transmission with CS and without CS method. Simulation confirms that our method reduces the number of transmissions significantly.