On In-network Synopsis Join Processing for Sensor Networks

The emergence of sensor networks enables applications that deploy sensors to collaboratively monitor environment and process data collected. In some scenarios, we are interested in using join queries to correlate data stored in different regions of a sensor network, where the data volume is large, making it prohibitive to transmit all data to a central server for joining. In this paper, we present an in-network synopsis join strategy for evaluating join queries in sensor networks with communication efficiency. In this strategy, we prune data that do not contribute to the join results in the early stage of the join processing, therefore reducing unnecessary communication overhead. In our simulation-based experiments, we study the performance of synopsis join for different join selectivities and investigate the impact synopsis accuracy and message loss. The results show that synopsis join outperforms the centralized join scheme in terms of communication cost, especially for low join selectivities, thus prolonging the lifetime of the sensor network.