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首页> 外文期刊>International Journal of Computer Systems Science & Engineering >Closest pair queries in spatio-temporal databases
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Closest pair queries in spatio-temporal databases

机译:时空数据库中最接近的对查询

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摘要

In recent years, spatio-temporal databases have been studied intensively. This paper proposes how to process k closest pair queries in spatio-temporal databases for the first time. A spatio-temporal k closest pair query continuously searches the k closest pairs between a set of spatial objects and a set of moving objects for a specified time interval of the query. To maintain the order of the kclosest pairs, we use a time function that can represent the change in distance between a spatial object and a moving object as time passes. For efficient processing of k closest pair queries, we present an event-based structure, instead of a simple split list structure to avoid unnecessary computations, along with a distance bound used to prune unnecessary node accesses. Our event-based method is 9 to 43 times faster, compared to a method using a simple split list structure. Also, our event-based structure can be applied to process spatio-temporal k nearest neighbor queries. In various experiments, our event-based approach is 11 to 46 times faster than an existing approach for processing spatio-temporal k nearest neighbor queries.
机译:近年来,对时空数据库进行了深入研究。本文提出了如何首次在时空数据库中处理k个最接近的对查询。时空k最接近对查询在查询的指定时间间隔内连续搜索一组空间对象和一组运动对象之间的k个最接近对。为了保持最接近的对的顺序,我们使用时间函数来表示空间对象和运动对象之间的距离随时间的变化。为了有效处理k个最接近的对查询,我们提出了一个基于事件的结构,而不是一个简单的拆分列表结构,以避免不必要的计算,以及用于修剪不必要的节点访问的距离限制。与使用简单拆分列表结构的方法相比,我们的基于事件的方法快9到43倍。同样,我们基于事件的结构可以应用于处理时空k最近邻查询。在各种实验中,我们基于事件的方法比处理时空k最近邻查询的现有方法快11到46倍。

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