Compressive and Cooperative Sensing in Distributed Mobile Sensor Networks

In this paper, we propose an algorithm to support distributed mobile sensors to collect data in sensing areas needing to be observed. The algorithm exploits random positions of mobile sensors to measure the area and applies compressive sensing (CS) to reconstruct all sensed data based on a certain number of CS measurements. At a time instant, the sensors add all readings within their sensing range and exchange their accumulative readings to their neighbors within a sensor communication range. Each CS measurement created at a time is a sum of all data measured by a group of connected sensors. We further analyze and formulate expression for power consumption for communications in the network. The measurement matrix, the number of mobile sensors, the sensing range and the communication range are analyzed and suggested for the networks to consume the least power.