• DocumentCode
    1850021
  • Title

    Improving Sort-Tile-Recusive algorithm for R-tree packing in indexing time series

  • Author

    Bui Cong Giao ; Duong Tuan Anh

  • Author_Institution
    Fac. of Comput. Sci. & Eng., Ho Chi Minh City Univ. of Technol., Ho Chi Minh City, Vietnam
  • fYear
    2015
  • fDate
    25-28 Jan. 2015
  • Firstpage
    117
  • Lastpage
    122
  • Abstract
    The Sort-Tile-Recursive (STR) algorithm is a simple and efficient bulk-loading method for spatial or multidimensional data management using R-tree. In this paper, we put forward an approach to improve the STR algorithm for packing R-trees in indexing time series by some strategies choosing coordinates to partition spatial objects into nodes of R-trees. Every strategy has its own method to connect ends of consecutive runs into a suboptimum space-filling curve. We will compare the proposed approach with previous works in terms of space storing the index structure and runtime for range search on R-trees. Extensive experiments are carried out on many streaming time series datasets to evaluate our improved STR methods and previous methods unbiasedly and precisely. The experimental results show that the improved STR methods outperform previous methods.
  • Keywords
    database indexing; sorting; time series; tree data structures; visual databases; R-tree packing; R-trees nodes; STR algorithm; bulk-loading method; index structure; indexing; multidimensional data management; sort-tile-recusive algorithm; space storing; spatial data management; spatial objects partition; suboptimum space-filling curve; time series datasets; Algorithm design and analysis; Arrays; Discrete Fourier transforms; Indexes; Loading; Partitioning algorithms; Vegetation; R-tree; Sort-Tile-Recursive; bulk-loading; index structure;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing & Communication Technologies - Research, Innovation, and Vision for the Future (RIVF), 2015 IEEE RIVF International Conference on
  • Conference_Location
    Can Tho
  • Print_ISBN
    978-1-4799-8043-7
  • Type

    conf

  • DOI
    10.1109/RIVF.2015.7049885
  • Filename
    7049885