Indexing spatial data in cloud data managements

Ling Yin Wei, Ya Ting Hsu, Wen Chih Peng, Wang-chien Lee

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

With the proliferation of smart phones and location-based services, the amount of data with spatial information, referred to as spatial data, is dramatically increasing. Cloud computing plays an important role handling large-scale data analysis, and several cloud data managements (CDMs) have been developed for processing data. CDMs usually provide key-value storage, where each key is used to access its corresponding value. However, user-generated spatial data are usually distributed non-uniformly. In this paper, we present a novel key design based on an R+-tree (KR+-index) for retrieving skewed spatial data efficiently. In the experiments, we implement the KR+-index on Cassandra, and study its performance using spatial data. Experiments show that the KR+-index outperforms the-state-of-the-art methods.

Original languageEnglish (US)
Pages (from-to)48-61
Number of pages14
JournalPervasive and Mobile Computing
Volume15
DOIs
StatePublished - Dec 1 2014

Fingerprint

Spatial Data
Data Management
Indexing
Information management
Location based services
Cloud computing
Experiments
R-tree
Spatial Information
Proliferation
Cloud Computing
Experiment
Data analysis

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications
  • Applied Mathematics

Cite this

Wei, Ling Yin ; Hsu, Ya Ting ; Peng, Wen Chih ; Lee, Wang-chien. / Indexing spatial data in cloud data managements. In: Pervasive and Mobile Computing. 2014 ; Vol. 15. pp. 48-61.
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Indexing spatial data in cloud data managements. / Wei, Ling Yin; Hsu, Ya Ting; Peng, Wen Chih; Lee, Wang-chien.

In: Pervasive and Mobile Computing, Vol. 15, 01.12.2014, p. 48-61.

Research output: Contribution to journalArticle

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