移动点对象HR索引及反向最近邻查询

在此提出了一种基于速度分布的HR树索引结构，首先在速度域中对移动对象集进行规则划分，根据速度标量大小将移动对象划分到不同的速度树中，每棵速度树中移动对象具有相近的速度；对每棵速度树中的移动对象，则利用时间间隔进行划分。HR树索引增加了两个分别建于叶节点和根节点之上的Hash辅助索引结构，并基于HR树提出了反向最近邻查询算法，具有很好的动态更新性能和并发性。实验结果与分析表明，基于HR树索引的反向最近邻查询算法具有良好的更新及查询性能，优于通用的TPR树索引。

HR Indexing of Moving Point Objects and Reverse Nearest Neighbors Query

In this paper a HR indexing structure, which is based on the velocity distribution is presented for moving objects with frequent updates and sorts. First the velocity domain is split regularly, and moving objects are classified into different trees by their velocities, thus the moving objects in one tree have similar velocities. The moving objects are classified by time interval in one tree. To support frequent updates two sypplemented hash indexes on leaf nodes and root nodes separately are added to HR-tree. Also a reverse nearest neighbors query algorithm is developed for HR-tree. Thus having a good dynamic update performance and concurrency. Experimental results and analysis show that the reverse nearest neighbors query algorithm for HR-tree has a good update and query performance and outperforms the popular TPR tree index.