首页> 外文会议>Twenty-ninth International Conference on Very Large Databases; Sep 9-12, 2003; Berlin, Germany >The TPR*-Tree: An Optimized Spatio-Temporal Access Method for Predictive Queries
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The TPR*-Tree: An Optimized Spatio-Temporal Access Method for Predictive Queries

机译:TPR *-树:用于预测查询的优化时空访问方法

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A predictive spatio-temporal query retrieves the set of moving objects that will intersect a query window during a future time interval. Currently, the only access method for processing such queries in practice is the TPR-tree. In this paper we first perform an analysis to determine the factors that affect the performance of predictive queries and show that several of these factors are not considered by the TPR-tree, which uses the insertion/deletion algorithms of the R*-tree designed for static data. Motivated by this, we propose a new index structure called the TPR*-tree, which takes into account the unique features of dynamic objects through a set of improved construction algorithms. In addition, we provide cost models that determine the optimal performance achievable by any data-partition spatio-temporal access method. Using experimental comparison, we illustrate that the TPR*-tree is nearly-optimal and significantly outperforms the TPR-tree under all conditions.
机译:预测性时空查询检索在将来的时间间隔内将与查询窗口相交的一组移动对象。当前,实际上,用于处理此类查询的唯一访问方法是TPR树。在本文中,我们首先进行分析以确定影响预测查询性能的因素,并表明TPR树未考虑其中一些因素,而TPR树使用了R *树的插入/删除算法,静态数据。为此,我们提出了一种称为TPR * -tree的新索引结构,该索引结构通过一组改进的构造算法考虑了动态对象的独特功能。此外,我们提供了成本模型,该模型确定了通过任何数据分区时空访问方法可实现的最佳性能。通过实验比较,我们说明了TPR *树几乎是最佳的,并且在所有条件下均明显优于TPR树。

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