A new enhancement to the R-tree node splitting

Abstract

The performance of spatial queries depends mainly on the underlying index structure used to handle them. R-tree, a well-known spatial index structure, suffers largely from high overlap and high coverage resulting mainly from splitting the overflowed nodes. Assigning the remaining entries to the underflow node in order to meet the R-tree minimum fill constraint ( Remaining Entries problem) may induce high overlap or high coverage. This is done without considering the geometric features of the remaining entries and this may cause a very non-optimized expansion of that particular node. This paper presents a solution to the above problem. The proposed solution to this problem distributes rectangles as follows: (1) assign m entries to the first node, which are nearest to the first seed; (2) assign other m entries to the second node, which are nearest to the second seed; (3) assign the remaining entries one by one to the nearest seed. Several experiments on real data, as well as synthetic data, show that the proposed splitting algorithm outperforms the efficient version of the original R-tree in terms of query performance.

To sort or not to sort: the evaluation of R-Tree and B+-Tree in transactional environment with ordered result requirement

“…This study prompted a wave of research papers and one can say that it gave birth to the new area of research. This research related to development of the new R-Tree variants [1,8,9], niche approaches [6,9], split techniques [10][11][12], concurrency techniques [13,14] etc. The study [6] states that there are several dozens of R-Tree variants.…”

A New Double Sorting-Based Node Splitting Algorithm for R-Tree

“…The coverage of a split is a total area of bounding rectangles. In general smaller coverage leads to the smaller probability of multipath queries when query area is relatively large [1].…”

A new double sorting-based node splitting algorithm for R-tree

“…Spatial objects in R tree are approximated by minimal bounding rectangles (MBRs), see Fig. [1]. Leaf node entry of R tree con tains MBR of spatial object and a reference to the cor responding database object.…”

“…R tree was originally designed for access to multidi mensional data, but it is also applied for one dimen sional intervals [10]. 1 The article is published in the original.…”

“…The cover age of a split is a total area of bounding rectangles. In general smaller coverage leads to the smaller prob ability of multipath queries when query area is rela tively large [1].…”