Finding similar answers in data-centric sensor networks

Intensive study has been dedicated to wireless sensor networks and their applications in the last few years. However, similarity search problem in sensor network environments seems to have not attracted the deserved attention. In fact, sensor detected data are very likely imprecise due to the simplified hardware of the sensor itself and various environmental factors. Hence, queries requesting for similar result should be an often scenario and an important problem to resolve. In this paper, we propose a Similarity Search Algorithm (SSA) for efficiently processing similarity search queries. We first present a data-centric storage structure based on the concept of Hilbert curve. Then, we propose an algorithm designed for efficiently probing the most similar data item for the sensor network. The performance study reveals that this mechanism is highly efficient and significantly outperforms other approaches in processing similarity search queries.