机构地区: 华南理工大学计算机科学与工程学院
出 处: 《计算机工程》 2009年第7期42-45,48,共5页
摘 要: 为解决大量移动对象位置频繁更新所带来的性能下降问题,提出一种基于改进的Quadtree和Hash表的QH全时态索引结构。这种新的索引结构可以支持移动对象全时态索引,在Hash表中通过存储移动对象指针来支持移动对象标识查询,并对Quadtree的叶子节点采用适时合并的方法来防范分支太深而造成的查询效率低下。实验证明,QH索引与TPR-tree相比,移动对象的更新效率更高、对象标识查询较优、范围查询性能相近。 Traditional index structures do not work well on moving objects because of the need of frequently updating the index which leads to the poor performance. This paper presents a novel indexing structure based on Quadtree and Hash table, namely the QH-index which can index the past, present and future positions of moving object and can support moving object's range queries and point queries which include the object identifier based query. Merging timely the corresponding nodes to degrade the depth of the tree can guarantee the query efficiency. Experiments show that the QH-index gains much better performance in updating and in querying by the object identifier than those of the TPR-tree, and the efficiency of range query is no less than that of TPR-tree.
领 域: [自动化与计算机技术] [自动化与计算机技术]