Data gathering in wireless sensor network for energy efficiency with and without compressive sensing at sensor node

Main constraints of wireless sensor networks (WSN) are less memory space, limited power supply, processing speed and availability of bandwidth for communication. The most important challenge in wireless sensor networks is to design energy-efficient data gathering network which increases the life time of wireless sensor networks. In various studies, it is observed that processed data requires less power as compared to transmitting data in the wireless medium. Hence, it is more significant to apply compressed sensing algorithm at sensing node. Also, if Compressed Sensing (CS) is used with clustering method it will give significant power saving in wireless sensor networks (WSN). In this paper, we addressed comparison between energy saving obtained by changing random compressive sensing samples and without compressive sensing.