Indexing spatial data in cloud data managements

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

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


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
StatePublished - Dec 1 2014

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications


Dive into the research topics of 'Indexing spatial data in cloud data managements'. Together they form a unique fingerprint.

Cite this