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Efficient evaluation of continuous spatio-temporal queries on moving objects with uncertain velocity

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Abstract

Continuous Range (CR) query and Continuous K-Nearest Neighbor (CKNN) query are two important types of spatio-temporal queries. Given a time interval [t s , t e ] and a moving query object q, a CR query is to find the moving objects whose Euclidean distances to q are within a user-given distance at each time instant within [t s , t e ]. A CKNN query is to retrieve the K-Nearest Neighbors (KNNs) of this query object q at each time instant within [t s , t e ]. In this paper, we investigate how to process these spatio-temporal queries efficiently under the situation that the velocity of each object is not fixed. This uncertainty on the velocity of object inevitably results in high complexity in processing spatio-temporal queries. We will discuss the complications incurred by this uncertainty and propose two algorithms, namely the Possibility-based possible within objects searching algorithm and the Possibility-based possible KNN searching algorithm, for the CR query and the CKNN query, respectively. A Possibility-based model is designed accordingly to quantify the possibility of each object being the result of a CR query or a CKNN query. Comprehensive experiments are performed to demonstrate the effectiveness and the efficiency of the proposed approaches.

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Acknowledgements

This work was supported by National Science Council of Taiwan (R.O.C.) under Grants NSC96-2221-E-006-260-MY2 and NSC96-2221-E-006-261-MY2.

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  1. Department of Computer Science and Information Engineering, National Cheng-Kung University, Tainan, Taiwan, Republic of China

    Yuan-Ko Huang & Chiang Lee

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  1. Yuan-Ko Huang
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  2. Chiang Lee
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Correspondence to Chiang Lee.

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Huang, YK., Lee, C. Efficient evaluation of continuous spatio-temporal queries on moving objects with uncertain velocity. Geoinformatica 14, 163–200 (2010). https://doi.org/10.1007/s10707-009-0081-8

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