Querying about the past, the present, and the future in spatio-temporal databases

Jimeng Sun, Dimitris Papadias, Yufei Tao, Bin Liu

Research output: Contribution to conferencePaperpeer-review

Abstract

Moving objects (e.g., vehicles in road networks) continuously generate large amounts of spatio-temporal information in the form of data streams. Efficient management of such streams is a challenging goal due to the highly dynamic nature of the data and the need for fast, on-line computations. In this paper we present a novel approach for approximate query processing about the present, past, or the future in spatio-temporal databases. In particular, we first propose an incrementally updateable, multi-dimensional histogram for present-time queries. Second, we develop a general architecture for maintaining and querying historical data. Third, we implement a stochastic approach for predicting the results of queries that refer to the future. Finally, we experimentally prove the effectiveness and efficiency of our techniques using a realistic simulation.

Original languageEnglish (US)
Pages202-213
Number of pages12
DOIs
StatePublished - Jun 1 2004
Externally publishedYes
EventProceedings - 20th International Conference on Data Engineering - ICDE 2004 - Boston, MA., United States
Duration: Mar 30 2004Apr 2 2004

Other

OtherProceedings - 20th International Conference on Data Engineering - ICDE 2004
CountryUnited States
CityBoston, MA.
Period3/30/044/2/04

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems

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