PBS: A Virtual Grid Architecture for Gradient-based Active Querying in Sensor Networks

摘要

Every physical event diffuses its effect geographically, which results in perceivable information gradient within the proximity of the phenomenon. In this paper, we propose a novel framework for on-demand query processing that exploits this diffusion property to form a virtual grid-based querying architecture, Probe-before-Spray (PBS), for wireless sensor networks. PBS effectively divides the sensor field on-demand based on the query type and parameters in addition to the gradient spread. Also, it combines gradient routing and in-network processing for efficient and scalable querying in sensor networks. Based on PBS, we design new algorithms to process basic aggregate queries - count, sum, average, max and min, and combined queries. Through analysis, we analyze the worst-case overhead to process these queries using PBS. Also, using extensive simulations, we demonstrate that PBS helps to reduce search overhead significantly (over 30%) to process such queries while attaining accuracy over 99%.