A novel approach for information discovery in wireless sensor grids

Multi-dimensional Wireless sensor grids (WSG)s are deployed in complex environments to sense and collect data relating to multiple attributes (multi-dimensional data). Such networks present unique challenges to data dissemination, data storage of in-network information discovery. However, in order to fully exploit these networks for mission-critical applications, energy-efficient and scalable solutions for information discovery are essential. In this paper, we propose a novel and adaptive method for information discovery for multi-dimensional WSGs that can significantly increase network lifetime and minimize query processing latency, resulting in quality of service improvements that are of immense benefit to mission-critical applications. Further, we investigate efficient strategies for information discovery in large-scale wireless sensor networks and propose the Adaptive Multi-Dimensional Multi-Resolution Architecture (A-MDMRA) that efficiently combines “push” and “pull” strategies for information discovery. The A-MDMRA also adapts to variations in the frequencies of events and queries in the network to construct optimal routing structures. We present simulation results to show that the proposed approach to information discovery offers significant improvements on query resolution latency compared with current approaches. We observe that our proposed methods outperform existing schemes such as double rulings, comb needle and Time-Parameterized Data Centric Storage by up to 14% in terms of query resolution latency and up to 20% in terms of energy-efficiency.