The xBR\(^+\)-tree: An Efficient Access Method for Points

  • George Roumelis
  • Michael VassilakopoulosEmail author
  • Thanasis Loukopoulos
  • Antonio Corral
  • Yannis Manolopoulos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9261)


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.


Spatial access methods Quadtrees xBR-trees Query processing. 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • George Roumelis
    • 1
  • Michael Vassilakopoulos
    • 2
    Email author
  • Thanasis Loukopoulos
    • 3
  • Antonio Corral
    • 4
  • Yannis Manolopoulos
    • 1
  1. 1.Department of InformaticsAristotle University of ThessalonikiThessalonikiGreece
  2. 2.Department of Electrical and Computer EngineeringUniversity of ThessalyVolosGreece
  3. 3.Department of Computer Science and Biomedical InformaticsUniversity of ThessalyLamiaGreece
  4. 4.Department of InformaticsUniversity of AlmeriaAlmeriaSpain

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