Neighborhood based data collection in Wireless Sensor Networks employing Compressive Sensing

The integration between data collection methods in Wireless Sensor Networks (WSNs) and Compressive Sensing (CS) provides energy efficient paradigms. In this paper, we propose an algorithm to gather sensory data based on sensor neighborhoods in such networks for further energy saving purposes. The CS measurements created from random neighborhoods are sent to the base-station (BS). The BS implements a CS reconstruction algorithm to recover all raw sensor readings precisely based on a certain number of measurements. Both one-hop and multi-hop transmissions to forward CS measurements from each sensor neighborhood to the BS are considered. All consumed power elements with data collection are formulated and compared in simulation.