Using Pre-aggregation for Efficient Spatial Query Processing in Sensor Environments

Many applications using sensing data require the fast retrieval of aggregated information in sensor networks. In this paper, distributed spatial index structure in sensor networks for time-efficient aggregation query processing is proposed. The main idea is to logically organize sensors in underlying networks into distributed R-Tree structure, named Sensor Tree. Each node of the Sensor Tree has pre-aggregated results which are the collection of the values of aggregated result for sensing data of the same type of sensors within Minimum Bounding Rectangle (MBR). If a spatial region query is required, the processing of the query searches the location of the target sensor from the root of the Sensor Tree. And then it finally sends the values of pre-aggregated result of that sensor. By the proposed Sensor Tree aggregation query processing on any region, response time and energy consumption can be reduced since it avoids flooding query to the leaf sensor or non-relevant sensors in the sensor networks.