Thresholded Range Aggregation in Sensor Networks

The recent advances in wireless sensor technologies (e.g., Mica, Telos motes) enable the economic deployment of lightweight sensors for capturing data from their surrounding environment, serving various monitoring tasks, like forest wildfire alarming and volcano activity. We propose a novel query called thresholded range aggregate query (TRA), which retrieves the IDs of the sensors for which the average measurement in their neighborhood exceeds a user-given threshold. This query provides results that they are robust against individual sensor abnormality, and yet precisely summarize the sensors' status in each local region. In order to process the (snapshot) TRA query, we develop energy-efficient protocols based on appropriate operators and filters in sensor nodes. The design of these operators and filters is non-trivial, due to the fact that each sensor measurement influences the actual results of other nodes in its neighborhood region. Furthermore, we extend our protocols for continuous evaluation of the TRA query. Experimental results show that our proposed solutions indeed offer substantial energy savings for both real and synthetic sensor networks.