一种改进的R-树节点分裂优化算法  

An Improved R-tree Node Splitting Optimization Algorithm

作　　者：贺建英 HE Jianying(School of Intelligent Manufacturing,Sichuan University of Arts and Science,Dazhou 635000,China)

机构地区：[1]四川文理学院智能制造学院,四川达州635000

出　　处：《现代信息科技》2020年第22期86-90,94,共6页Modern Information Technology

基　　金：四川革命老区发展研究中心重点项目(SLQ2020SA-01);四川文理学院重点项目(2018KZ001Z);四川文理学院教改项目(2020JZ001)。

摘　　要：对R-树空间索引查询效率低下的问题,提出一种改进的PSR-树索引方法。PSR-树使用贪心算法找到要分裂的节点中对应的MBR的最小边界值,在最小边界值和非最小边界值中分别随机选择一个边界对象,用选择得到的这两个对象为分裂后两个新增节点首选空间数据对象进行分裂操作,建立好PSR-树后并写入节点。实验表明,PSR-树可以有效地减少节点中最小外接矩形的重叠面积,时间响应上比已有的R-树索引快,PSR-树从上述两个方面提高了查询效率。To solve the problem of low efficiency of R-tree space index query,an improved PSR-tree index method is proposed.The PSR-tree uses a greedy algorithm to find the minimum boundary value of the corresponding MBR in the node to be split.A boundary object is randomly selected from the minimum boundary value and the non-minimum boundary value,use the selected two objects to perform the split operation for the two newly-added node preferred spatial data objects after splitting,and then write the node after the PSR-tree is established.The experiment shows that PSR-tree can effectively reduce the overlap area of the MBR in the node,and the time response is faster than the existing R-tree index,PSR-tree improves the query efficiency from these two aspects.

关 键 词：R-树 最小外接矩形 节点分裂 最小边界值 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] TP301.6[自动化与计算机技术—计算机科学与技术]