泛在环境下运动目标轨迹时空聚合的aCN-RB-tree更新方法

Dong-Wook Lee, S. Baek, Hae-Young Bae
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引用次数: 8

摘要

在无处不在的环境中,移动对象管理在交通、物流和数据挖掘等应用中非常流行。我们之前的研究主要集中在aCN-RB-tree约束网络中轨迹时空聚合的有效索引结构。它利用基于约束网络的索引对轨迹的聚合值进行管理。同时,它还支持轨迹方向、交通区域和时间间隔轨迹的高效搜索。本文提出了考虑运动目标特征的aCN-RB-tree更新方法。该方法将运动对象数据按面积和时间分割,从而有效地更新了索引。它支持无处不在的交通管理系统和采矿系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
aCN-RB-tree: Update Method for Spatio-Temporal Aggregation of Moving Object Trajectory in Ubiquitous Environment
Moving object management is popular with traffic, logistic and data mining applications in ubiquitous environment. Our previous research focused on efficient index structure for spatio-temporal aggregation of trajectory in a constrained network, named aCN-RB-tree. It manages aggregation values of trajectories using constraint network based index. Also, it supports direction of trajectory, efficient search for traffic zone and trajectory of the time interval. In this paper, we proposed update method of aCN-RB-tree, considering moving object features. The method updates index efficiently as it divided moving object data by area and time. It supports traffic management systems and mining systems in ubiquitous environment.
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