11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA'05) (2005)
Hong Kong, China
Aug. 17, 2005 to Aug. 19, 2005
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/RTCSA.2005.15
Song Han , City University of Hong Kong
Edward Chan , City University of Hong Kong
Reynold Cheng , Purdue University
Kam-Yiu Lam , City University of Hong Kong
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.
S. Han, E. Chan, K. Lam and R. Cheng, "A Statistics-Based Sensor Selection Scheme for Continuous Probabilistic Queries in Sensor Networks," 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA'05)(RTCSA), Hong Kong, China, 2005, pp. 331-336.