关于连续监测top-k不安全移动物体

Jian Wen, V. Tsotras
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引用次数: 2

摘要

随着位置跟踪系统的广泛应用,连续跟踪移动物体之间的位置变化是可能的,并且对许多实际应用非常重要。本文提出了一种新的基于位置的连续查询,称为连续top-k不安全移动对象查询(CTUO)。该查询连续监控k个最不安全的移动物体,其中物体(被保护人)的不安全性由其安全要求与周围保护力(保护人)提供的保护之间的差异来定义。与传统的top-k查询(对象的分数代表其自身特征)相比,CTUO描述了被保护者和被保护者之间的关系,这引入了计算挑战,因为天真地需要检查所有对象来回答这样的查询。为了避免这一问题,基于阈值算法的基本剪剪技术,提出了GridPrune和GridPrune- pro两种高效的剪剪算法。实验表明,本文提出的算法在I/O节省上比原始解决方案节省了近两个数量级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On continuous monitoring top-k unsafe moving objects
With the wide usage of location tracking systems, continuously tracking relationships among moving objects over their location changes is possible and important to many real applications. This paper proposes a novel continuous location-based query, called the continuous top-k unsafe moving objects query or CTUO. This query continuously monitors the k most unsafe moving objects, where the unsafety of an object (protectee) is defined by the difference between its safety requirement and the protection provided by protection forces (protectors) around it. Compared with the traditional top-k queries where the score of an object represents its own characteristics, CTUO describes the relationships between protectees and protectors, which introduces computational challenges since naively all objects should be inspected to answer such a query. To avoid this, two efficient algorithms, GridPrune and GridPrune-Pro, are proposed based on the basic pruning technology from the Threshold Algorithm. Experiments show that the proposed algorithms outperform the naive solution with nearly two orders of magnitude on I/O savings.
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