Query similarity index based query preprocessing mechanism for multiapplication sharing wireless sensor networks

In multiapplication sharing wireless sensor networks, various application queries exhibit similarity in their spatial, temporal, and sensing attribute requirements, thus result in redundant sensing tasks. The dissemination and execution of such redundant sensing tasks cause network traffic overhead and quick energy drop of the sensor nodes. Existing task scheduling and allocation mechanisms focus on reducing upstream traffic by maximizing data sharing among sensing tasks. However, downstream traffic due to sensing tasks dissemination plays a crucial role in large-scale WSNs and required to be addressed. This paper proposes a query similarity index based query preprocessing mechanism that prevents the generation of redundant sensing tasks by creating a common query corresponding to the overlapping functional requirements of the queries and reduces the downstream as well as upstream traffic significantly. The performance evaluation reveals approximately 60% reduction in downstream traffic, 20–40% reduction in upstream traffic, and 40% reduction in energy consumption when compared with state-of-the-art mechanisms.