The xbr+-tree: An efficient access method for points

12Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Spatial indexes, such as those based on Quadtree, are important in spatial databases for efficient execution of queries involving spatial constraints. In this paper, we present improvements of the xBR-tree (a member of the Quadtree family) with modified internal node structure and tree building process, called xBR+-tree. We highlight the differences of the algorithms for processing single dataset queries between the xBR and xBR+-trees and we demonstrate performance results (I/O efficiency and execution time) of extensive experimentation (based on real and synthetic datasets) on tree building process and processing of single dataset queries, using the two structures. These results show that the two trees are comparable, regarding their building performance, however, the xBR+-tree is an overall winner, regarding spatial query processing.

Cite

CITATION STYLE

APA

Roumelis, G., Vassilakopoulos, M., Loukopoulos, T., Corral, A., & Manolopoulos, Y. (2015). The xbr+-tree: An efficient access method for points. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9261, pp. 43–58). Springer Verlag. https://doi.org/10.1007/978-3-319-22849-5_4

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free