Time-Parameterized Queries in Spatio-Temporal Databases

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Time-Parameterized Queries in Spatio-Temporal Databases (2002)

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by Yufei Tao , Dimitris Papadias

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@MISC{Tao02time-parameterizedqueries,
    author = {Yufei Tao and Dimitris Papadias},
    title = {Time-Parameterized Queries in Spatio-Temporal Databases},
    year = {2002}
}

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Abstract

Time-parameterized queries (TP queries for short) retrieve (i) the actual result at the time that the query is issued, (ii) the validity period of the result given the current motion of the query and the database objects, and (iii) the change that causes the expiration of the result. Due to the highly dynamic nature of several spatio-temporal applications, TP queries are important both as standalone methods, as well as building blocks of more complex operations. However, little work has been done towards their efficient processing. In this paper, we propose a general framework that covers time-parameterized variations of the most common spatial queries, namely window queries, k-nearest neighbors and spatial joins. In particular, each of these TP queries is reduced to nearest neighbor search where the distance functions are def'med according to the query type. This reduction allows the application and extension of well-known branch and bound techniques to the current problem. The proposed methods can be applied with mobile queries, mobile objects or both, given a suitable indexing method. Our experimental evaluation is based on R-trees and their extensions for dynamic objects.

Keyphrases

time-parameterized query tp query spatio-temporal database standalone method mobile object validity period window query current problem dynamic object experimental evaluation several spatio-temporal application spatial join building block general framework suitable indexing method actual result neighbor search query type efficient processing time-parameterized variation complex operation k-nearest neighbor distance function current motion mobile query common spatial query little work bound technique well-known branch dynamic nature

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