Effective Management of High Rate Spatio-Temporal Queries in Wireless Sensor Networks

Handling high rate queries have always posed a challenge in wireless sensor networks (WSNs) owing to their resource constrained nature. This paper proposes a scheme that performs centralized and distributed optimization to improve the scalability of the high rate spatio-temporal queries in WSNs. Queries are optimized centrally based on multiple criteria such as spatial topological relationships, temporal and attribute correlations. An energy efficient load balanced clustered tree routing based on minimum bounding rectangle spatial indexing scheme is employed to aid the in-network optimization of queries. Two algorithms have been proposed to carry out a centralized and distributed optimization that works adaptively on queries switching between optimal and sub-optimal modes to handle multiple concurrent queries reliably. Simulation results show that the proposed scheme is highly scalable for large scale spatio-temporal queries and also has the added advantage of minimizing the energy consumption due to query and data transmission.