Spatio-temporal data services in a shared-nothing environment

Marios Hadjieleftheriou, Vassil Kriakov, Yangui Tao, George Kollios, Alex Delis, Vassilis J. Tsotras

Research output: Contribution to journalConference articlepeer-review


Recently, there has been a proliferation of applications that produce spatio-temporal data that has to be processed, stored and queried efficiently. These applications necessitate the execution of millions of updates in order to keep the underlying database up-to-date. Consequently, there is a need for spatio-temporal data management systems that are able to support such update intensive operations. Moreover, these systems should offer users the capability to examine present as well as past (historical) data versions in an on-line fashion. We propose a system that exploits the inherent parallelism of a shared-nothing computing environment for storing and indexing the spatio-temporal data. We describe our proposed system architecture, data organization, and outline techniques for ensuring robustness and scalability under excessive query loads and high update rates.

Original languageEnglish (US)
Pages (from-to)131-134
Number of pages4
JournalProceedings of the International Conference on Scientific and Statistical Database Management, SSDBM
StatePublished - 2004
EventProceedings - 16th International Conference on Scientific and Statistical Databse Management, SSDBM 2004 - Santorini Island, Greece
Duration: Jun 21 2004Jun 23 2004

ASJC Scopus subject areas

  • Software
  • Applied Mathematics


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