Enhancing the Scalability of Non-Spatial Concurrent Queries in Wireless Sensor Networks

Handling large concurrent queries in an energy-efficient way always has been a critical problem in wireless sensor networks (WSNs) due to its resource-constrained nature. Many sensor applications use non-spatial queries for accessing precise sensor data at specific locations rather than spatial queries that retrieve data over a region. Though performing pre-optimization of queries externally is a common technique followed for sensor query optimization before it is optimized in-network; a detailed cost-based model for optimizing non-spatial queries has not yet been carried out effectively. This paper focuses on optimizing non-spatial queries through a bi-level multi-query optimization scheme that uses an elaborate cost model to compute the execution cost of different query plans. Further, in-network optimization is implemented to reduce the energy consumption due to query result transmissions. Experimental analysis shows that the proposed optimization reduces the overall energy consumption and increases the scalability of non-spatial concurrent queries.