TWINS: Efficient time-windowed in-network joins for sensor networks

Wireless sensor networks (WSNs) have recently received a lot of attention and several techniques have been proposed for in-network join processing. Since sensor readings are continuously collected and it is interesting to track the relationships between sensor readings in order to detect the events of interest, the in-network joins with time windows are very important for WSNs. Most of existing techniques on in-network join processing for sensor networks transmit sensor readings redundantly in a time window and result in a lot of unnecessary energy consumption. In this paper, we propose the energy-efficient time-windowed in-network join algorithm for Sensor networks (TWINS). We devise three optimization rules to reduce redundant transmissions of sensor data effectively by using compact representations of time durations and join attribute values. We conduct extensive experiments using synthetic and real-life data sets. Our experimental results confirm that the energy consumption of TWINS is much smaller than that of the existing state-of-the-art algorithms for time-windowed in-network joins.