Collaborative Data Gathering in Wireless Sensor Networks Using Measurement Co-Occurrence

Data gathering is a basic activity of many wireless sensor network applications. We propose a novel collaborative data gathering approach utilizing data co-occurrence, which is different from data correlation. Our approach offers a trade-off between communication costs of data gathering versus errors at estimating the sensor measurements at the base station, by having sensors with co-occurring measurements alternate in transmitting such measurements to the base station, and having the base station make inferences about sensor measurements utilizing only the transmitted data. We describe two effective methods for in- network detecting measurements co-occurrence among sensors, an efficient protocol for scheduling the transmission of measurements, and a simple algorithm for measurement inference. Our simulation results on synthetic and real datasets show a substantial (up to 65%) reduction on the communication costs of data gathering with few number of inference errors (< 6%) at the base station.