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Processing Proximity Relations in Road Networks

机译:处理公路网络的邻近关系

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Applications ranging from location-based services to multi-player online gaming require continuous query support to monitor, track, and detect events of interest among sets of moving objects. Examples are alerting capabilities for detecting whether the distance, the travel cost, or the travel time among a set of moving objects exceeds a threshold. These types of queries are driven by continuous streams of location updates, simultaneously evaluated over many queries. In this paper, we define three types of proximity relations that induce location constraints to model continuous spatio-temporal queries among sets of moving objects in road networks. Our focus lies on evaluating a large number of continuous queries simultaneously. We introduce a novel moving object indexing technique that together with a novel road network partitioning scheme restricts computations within the partial road network. These techniques reduce query processing overhead by more than 95%. Experiments over real-world data sets show that our approach is twenty times faster than a baseline algorithm.
机译:应用范围从基于位置的服务到多人在线游戏都需要连续查询支持来监视移动物体集之间的感兴趣事件。示例是警报用于检测一组移动物体之间的距离,旅行成本或行驶时间是否超过阈值的警报能力。这些类型的查询由连续的位置更新驱动,同时在许多查询中进行评估。在本文中,我们定义了三种类型的接近关系,使得诱导位置约束来模拟道路网络中的移动物体集中的连续时空查询。我们的焦点在于同时评估大量连续查询。我们介绍一种新的移动物体索引技术,与新的道路网络分区方案一起限制部分道路网络内的计算。这些技术将查询处理耗尽超过95%。实验与现实世界数据集显示,我们的方法比基线算法快20倍。

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