Hana tree: A dynamic and robust access method for spatial data handling

Yongwon Kwon, Chang-Sung Jeong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we present a new multidimensional access method, called hana tree, which can provide an efficient and robust way for dynamic modifications and interactive queries to spatial database. We designed a new multidimensional binary encoding scheme, hana code, for representing points and page regions in hana tree. When a new spatial data is inserted in uncovered data space, the page region of the existing node is expanded to include it instead of creating a new one. These properties allow the decrease in the total number of nodes and the reduction in the number of nodes accessed during search, thus improving the overall performance in storage space utilization and various operations Also, we shall describe our experimental results where hana tree is compared to other point access methods to show the superiority of hana tree.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages271-283
Number of pages13
Volume1846
ISBN (Print)9783540676270
Publication statusPublished - 2000
Event1st International Conference on Web-Age Information Management, WAIM 2000 - Shanghai, China
Duration: 2000 Jun 212000 Jun 23

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1846
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other1st International Conference on Web-Age Information Management, WAIM 2000
CountryChina
CityShanghai
Period00/6/2100/6/23

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ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Kwon, Y., & Jeong, C-S. (2000). Hana tree: A dynamic and robust access method for spatial data handling. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1846, pp. 271-283). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1846). Springer Verlag.