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A Study of Update Methods for BoND-Tree Index on Non-ordered Discrete Vector Data

12 pagesPublished: March 9, 2020

Abstract

There is an increasing demand from numerous applications such as bioinformatics and cybersecurity to efficiently process various types of queries on datasets in a multidimensional Non-ordered Discrete Data Space (NDDS). An NDDS consists of vectors with values coming from a non-ordered discrete domain for each dimension. The BoND-tree index was recently developed to efficiently process box queries on a large dataset from an NDDS on disk. The original work of the BoND-tree focused on developing the index construction and query algorithms. No work has been reported on exploring efficient and effective up- date strategies for the BoND-tree. In this paper, we study two update methods based on two different strategies for updating the index tree in an NDDS. Our study shows that using the bottom-up update method can provide improved efficiency, comparing to the traditional top-down update method, especially when the number of dimensions for a vector that need to be updated is small. On the other hand, our study also shows that the two update methods have a comparable effectiveness, which indicates that the bottom-up update method is generally more advantageous.

Keyphrases: algorithm, database, multidimensional indexing, non ordered discrete data space, update

In: Gordon Lee and Ying Jin (editors). Proceedings of 35th International Conference on Computers and Their Applications, vol 69, pages 122-133.

BibTeX entry
@inproceedings{CATA2020:Study_Update_Methods_BoND,
  author    = {Ramblin Cherniak and Qiang Zhu and Sakti Pramanik},
  title     = {A Study of Update Methods for BoND-Tree Index on Non-ordered Discrete Vector Data},
  booktitle = {Proceedings of 35th International Conference on Computers and Their Applications},
  editor    = {Gordon Lee and Ying Jin},
  series    = {EPiC Series in Computing},
  volume    = {69},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/C4lK},
  doi       = {10.29007/3zq4},
  pages     = {122-133},
  year      = {2020}}
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