一种针对室内疏散的集成Hilbert曲线的R*树空间索引

基于位置的服务需要快速查询、插入和删除研究对象，这种需求在室内疏散相关的应用中被进一步加强，因此有必要引入空间索引优化针对室内空间对象的操作效能。在室内紧凑空间环境下，现有的空间索引效率较低，所以将R*树索引和Hilbert曲线相结合，提出了一种新型的集成Hilbert曲线的索引。将这种新型索引和标准R*树索引进行对比，结果表明，新索引能够显著提升多种空间操作效率。

A Hilbert-Curve-Based R* Tree Index Optimized for Indoor Evacuation

The location-based service requires fast query, insertion and deletion operations for research objects, and this demand is augmented for the indoor evacuation fields. Thus, introducing spatial index to tackle the operation efficiency problem is strongly demanded for indoor related scenes, and this method is sounding for indoor spatial objects. Nevertheless, this solution always meets a performance bottleneck. And this performance bottleneck of spatial index pervasively exists in the current compact indoor application scenes. To mitigate this problem, this paper tries to combine the R* tree index with the Hilbert curve, and proposes an innovative Hilbert curve based index. The succeeding experiment is designed to compare the performance of proposed index with the classic R* index. The test result shows the new index has successfully alleviated the execution efficiency for multi-type spatial operations, especially on critic indicators of spatial index performance.