Continuous answering holistic queries over sensor networks

Wireless sensor networks (WSNs) are widely used for various monitoring applications. Users issue queries to sensors and collect sensing data. Due to the low quality sensing devices or random link failures, sensor data are often noisy. In order to increase the reliability of the query results, continuous queries are often employed. In this work we focus on continuous holistic queries like median. Existing approaches are mainly designed for non-holistic queries like average. However, it is not trivial to answer holistic ones due to their non-decomposable property. We propose two schemes for answering queries under different data changing conditions. While sensor data changes slowly, based on the data correlation between different rounds, we propose one algorithm for getting the exact answers. When the data changing speed is high, we propose another approach to derive the approximate results. We evaluate both designs through extensive simulations. The results demonstrate that our approach significantly reduces the traffic cost compared with previous works while maintaining the same accuracy.