Similarity-aware query processing in sensor networks

We assume a sensor network with data-centric storage, where sensor data is stored within the sensor network and ad hoc queries are disseminated and processed inside the network. In such an environment, there are often similarities among submitted queries. Using current solutions, similar queries may have to go through the same expensive query processing steps thus wasting energy. In this paper, we propose a similarity-aware query processing scheme (SAQP) that materializes previous query results within the sensor network and utilizes these materialized results to answer future similar queries. Through simulation, we demonstrate that our SAQP scheme reduces energy consumption on queries with negligible increase in response time, and without compromising the quality of data