MDS: Efficient Multi-dimensional Query Processing in Data-Centric WSNs

摘要

Geographical hash table (GHT) has been widely used to provide energy efficiency for data-centric stor-age in wireless sensor networks. Such a mechanism, however, suffers from high communication cost when we apply multi-dimensional event search in the net-work. In this work, we present MDS, a flexible, com-plete, and efficient multi-dimensional search mecha-nism atop traditional GHT based data-centric storage architecture. MDS utilizes bloom filters to reduce the communication cost of in-network intersection and union operations for multi-dimensional queries in wireless sensor networks. This scheme can be easily extended to support multi-dimensional range queries. Our mathematical analysis indicates the optimal set-tings for the bloom filters that maximize the traffic sav-ings according to the information popularities. We conduct comprehensive simulations to evaluate our design. Results show that MDS achieves significant performance improvement in terms of energy consump-tions and thus improves the applicability of the multi-dimensional search over the GHT based data-centric storage in sensor networks.