Information discovery in multidimensional wireless sensor networks

Abstract

Wireless sensor networks (WSN) are attractive for information discovery in large-scale data rich environments and can add value to mission-critical applications such as battle-field surveillance, environmental monitoring and emergency response. However, in order to fully exploit these networks for such applications, energy-efficient and scalable solutions for information discovery are essential. Multidimensional WSNs are deployed in complex environments to sense and collect data relating to multiple attributes (multidimensional data). Such networks present unique challenges to data dissemination, data storage and in-network query processing (information discovery). In this paper, we propose a novel method of information discovery for multidimensional WSNs that can significantly increase network lifetime and minimize query processing latency, resulting in quality of service (QoS) improvements that are of immense benefit to mission-critical applications. We propose a distributed solution with multiple levels of resolution to enable fast query resolution. We present simulation results to show that the proposed approach to information discovery offers significant improvements on query resolution latency in comparison with current approaches. In addition, the results prove that the QoS improvements come with significant network-wide energy savings that will result in an increase of the network lifetime.