R-Tree for Phase Change Memory

Elkhan Jabarov1, Byung-Won On2, Gyu Sang Choi3 and Myong-Soon Park1

  1. Computer and Radio Communications Department, Korea University
    Seoul, Republic of Korea
    {ejabarov, myongsp}@korea.ac.kr
  2. Department of Statistics and Computer Science, Kunsan National University
    Kunsan, Republic of Korea
  3. Department of Information & Communication Engineering, Yeungnam University
    Yeungnam, Republic of Korea


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.

Key words

spatial database, spatial data, PCM, R -Tree, spatial tree, endurance, indexing algorithm

Digital Object Identifier (DOI)


Publication information

Volume 14, Issue 2 (June 2017)
Year of Publication: 2017
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Jabarov, E., On, B., Choi, G. S., Park, M.: R-Tree for Phase Change Memory. Computer Science and Information Systems, Vol. 14, No. 2, 347–367. (2017)