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Spatial Range Querying for Gaussian-Based Imprecise Query Objects

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3 Author(s)
Ishikawa, Y. ; Inf. Technol. Center, Nagoya Univ., Nagoya ; Iijima, Y. ; Yu, J.X.

In sensor environments and moving robot applications, the position of an object is often known imprecisely because of measurement error and/or movement of the object. In this paper, we present query processing methods for spatial databases in which the position of the query object is imprecisely specified by a probability density function based on a Gaussian distribution. We define the notion of a probabilistic range query by extending the traditional notion of a spatial range query and present three strategies for query processing. Since the qualification probability evaluation of target objects requires numerical integration by a method such as the Monte Carlo method, reduction of the number of candidate objects that should be evaluated has a large impact on query performance. We compare three strategies and their combinations in terms of the experiments and evaluate their effectiveness.

Published in:

Data Engineering, 2009. ICDE '09. IEEE 25th International Conference on

Date of Conference:

March 29 2009-April 2 2009