R -tree for phase change memory

Elkhan Jabarov, Byung Won On, Gyu Sang Choi, Myong Soon Park

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


Nowadays, many applications use spatial data for instance-location information, so storing spatial data is important.We suggest using R -Tree over PCM. Our objective is to design a PCM-sensitive R -Tree that can store spatial data as well as improve the endurance problem. Initially, we examine how R -Tree causes endurance problems in PCM, and we then optimize it for PCM. We propose doubling the leaf node size, writing a split node to a blank node, updating parent nodes only once and not merging the nodes after deletion when the minimum fill factor requirement does not meet. Based on our experimental results while using benchmark dataset, the number of write operations to PCM in average decreased by 56 times by using the proposed R -Tree. Moreover, the proposed R -Tree scheme improves the performance in terms of processing time in average 23% compared to R -Tree.

Original languageEnglish
Pages (from-to)347-367
Number of pages21
JournalComputer Science and Information Systems
Issue number2
Publication statusPublished - 2017 Jun

Bibliographical note

Publisher Copyright:
© 2017 ComSIS Consortium. All rights reserved.


  • Endurance
  • Indexing algorithm
  • PCM
  • R -Tree
  • Spatial data
  • Spatial database
  • Spatial tree

ASJC Scopus subject areas

  • General Computer Science


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