Article: Stochastic binary sensor networks for noisy environments Journal: International Journal of Sensor Networks (IJSNET) 2007 Vol.2 No.5/6 pp.414 - 427 Abstract: This paper proposes a stochastic framework for detecting anomalies or gathering events of interest in a noisy environment using a network consisting of binary sensors. A binary sensor is an extremely coarse sensor, capable of measuring data to only 1-bit accuracy. Our proposed stochastic framework employs a large number of inexpensive binary sensors operating in a noisy environment, yet collaboratively they are able to obtain accurate measurements. The main contributions of this paper are: (a) The theoretical accuracy analysis of the proposed stochastic binary sensor network in noisy environments, (b) an adaptive data collection framework based on the current measurements to reduce the energy consumption and (c) a novel coding scheme for energy-efficient routing. To quantify the performance of our proposed stochastic approach, we present the simulation results of two stochastic binary sensor networks for anomaly detection using our proposed coding scheme and adaptive data gathering framework. We demonstrate that our proposed framework can potentially reduce the energy consumption over the traditional approach by an order of magnitude. Inderscience Publishers - linking academia, business and industry through research

Title: Stochastic binary sensor networks for noisy environments

Authors: T. Nguyen, Dong Nguyen, Huaping Liu, Duc A. Tran

Addresses: School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, USA. ' School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, USA. ' School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, USA. ' Department of Computer Science, University of Dayton, Dayton, OH, USA

Abstract: This paper proposes a stochastic framework for detecting anomalies or gathering events of interest in a noisy environment using a network consisting of binary sensors. A binary sensor is an extremely coarse sensor, capable of measuring data to only 1-bit accuracy. Our proposed stochastic framework employs a large number of inexpensive binary sensors operating in a noisy environment, yet collaboratively they are able to obtain accurate measurements. The main contributions of this paper are: (a) The theoretical accuracy analysis of the proposed stochastic binary sensor network in noisy environments, (b) an adaptive data collection framework based on the current measurements to reduce the energy consumption and (c) a novel coding scheme for energy-efficient routing. To quantify the performance of our proposed stochastic approach, we present the simulation results of two stochastic binary sensor networks for anomaly detection using our proposed coding scheme and adaptive data gathering framework. We demonstrate that our proposed framework can potentially reduce the energy consumption over the traditional approach by an order of magnitude.

Keywords: stochastic binary sensors; sensor networks; noisy environments; energy efficiency; wireless networks; simulation; energy consumption.

DOI: 10.1504/IJSNET.2007.014365

International Journal of Sensor Networks, 2007 Vol.2 No.5/6, pp.414 - 427

Published online: 03 Jul 2007 *

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Title: Stochastic binary sensor networks for noisy environments

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