Quality Adjustable Query Processing Framework for Wireless Sensor Networks

Existing in-network query processing techniques are categorized as approximation and aggregation based approaches. The former achieves lower query response delay at the expense of accuracy, while the latter reduces query response inaccuracy by executing queries at the actual sensor nodes resulting in longer delay. In this paper, we propose a query processing framework which is delay as well as accuracy aware and capable of dynamic adjustment to meet user/application requirements. When query response is required within specific delay, it provides approximated sensor data meeting the delay requirement. On the other hand, when query response accuracy is vital, it tolerates longer delay in acquiring response with the desired accuracy. To achieve this, we propose a novel method of constructing a delay aware spanning tree (DAST) based on query load and organizing sensor data with varied accuracy. Experimental results illustrate superiority of the proposed framework against competing approaches.