基于受限移动对象当前及将来时刻检索的时空索引结构研究  

Indexing Approach for Querying About Present and Future Based on Constrained Moving Objects in Spatial-temporal Databases

作　　者：郭菁[1] 郭薇[2] 周洞汝[1] 

机构地区：[1]武汉大学计算机学院,湖北武汉430072 [2]上海交通大学电子信息与电气工程学院,上海200030

出　　处：《小型微型计算机系统》2007年第2期318-321,共4页Journal of Chinese Computer Systems

基　　金：国家自然科学基金项目(60173045)资助;国家"八六三"项目(2005AA122320)资助.

摘　　要：在给定的空间及时间范围内,如何构建高效的时空索引结构,以实现对移动对象快速有效的检索,是实现定位服务、智能交通、数字化战争等诸多应用中所迫切需要解决的问题.本文依据移动对象的运动特点,提出了一种面向当前及将来时刻快速更新及有效检索的索引结构—PQR树.PQR树是综合PMRQuad树和R*树的结构,首先依据道路分布用PMRQuad树将移动对象的索引空间实行粗略的层分割,将所有快速移动对象与道路相关联.然后用R*树索引分布在各个子空间块内的类静止对象.实验结果表明PQR树具有良好的更新和查询性能.In moving objects environment,last and efficiently indexing moving objects are a crucial issue in several application domains,such as LBS,Intelligence Transportation and Digital Battle. In this paper,based on the characters of moving objects,a new index structure,PQR-tree is proposed to fast update and efficiently index the positions of constrained moving objects on present and near future. PQR-tree is an integrated tree structure which combined PMR Quadtree and R ＊ -tree together. Firstly,a PMR quadtree is used to carry out rough level partition for index space of moving objects based on road networks and all last moving objects are related to the road networks. Then,an R ＊-tree is used to index quasi-static objects for each subspace. The experimental results show that PQR-tree achieves a better performance for both index updating and query evaluation.

关 键 词：移动对象 移动对象数据库 时空索引 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]