Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/19972
Title: A statistics-based sensor selection scheme for continuous probabilistic queries in sensor networks
Authors: Han, S
Chan, E
Cheng, R
Lam, KY
Keywords: Probability
Query processing
Sensor fusion
Statistical analysis
Issue Date: 2005
Publisher: IEEE
Source: 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, 2005 : proceedings : 17-19 August 2005, p. 331-336 How to cite?
Abstract: An approach to improve the reliability of query results based on error-prone sensors is to use redundant sensors. However, this approach is expensive; moreover, some sensors may malfunction and their readings need to be discarded. In this paper, we propose a statistical approach to decide which sensors to be used to answer a query. In particular, we propose to solve the problem with the aid of continuous probabilistic query (CPQ), which is originally used to manage uncertain data and is associated with a probabilistic guarantee on the query result. Based on the historical data values from the sensors, the query type, and the requirement on the query, we present methods to select an appropriate set of sensors and provide reliable answers for aggregate queries. Our algorithm is demonstrated in simulation experiments to provide accurate and robust query results.
URI: http://hdl.handle.net/10397/19972
ISBN: 0-7695-2346-3
ISSN: 1533-2306
DOI: 10.1109/RTCSA.2005.15
Appears in Collections:Conference Paper

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