Stream window join: Tracking moving objects in sensor-network databases

M. A. Hammad, W. G. Aref, Ahmed Elmagarmid

Research output: Chapter in Book/Report/Conference proceedingConference contribution

60 Citations (Scopus)

Abstract

The widespread use of sensor networks presents revolutionary opportunities for life and environmental science applications. Many of these applications involve continuous queries that require the tracking, monitoring, and correlation of multi-sensor data that represent moving objects. We propose to answer these queries using a multi-way stream window join operator. This form of join over multi-sensor data must cope with the infinite nature of sensor data streams and the delays in network transmission. The paper introduces a class of join algorithms, termed W-join, for joining multiple infinite data streams. W-join addresses the infinite nature of the data streams by joining stream data items that lie within a sliding window and that match a certain join condition. W-join can be used to track the motion of a moving object or detect the propagation of clouds of hazardous material or pollution spills over time in a sensor network environment. We describe two new algorithms for W-join, and address variations and local/global optimizations related to specifying the nature of the window constraints to fulfill the posed queries. The performance of the proposed algorithms are studied experimentally in a prototype stream database system, using synthetic data streams and real time-series data. Tradeoffs of the proposed algorithms and their advantages and disadvantages are highlighted, given variations in the aggregate arrival rates of the input data streams and the desired response times per query.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Scientific and Statistical Database Management, SSDBM
PublisherIEEE Computer Society
Pages75-84
Number of pages10
Volume2003-January
ISBN (Print)0769519644
DOIs
Publication statusPublished - 2003
Externally publishedYes
Event15th International Conference on Scientific and Statistical Database Management, SSDBM 2003 - Cambridge, United States
Duration: 9 Jul 200311 Jul 2003

Other

Other15th International Conference on Scientific and Statistical Database Management, SSDBM 2003
CountryUnited States
CityCambridge
Period9/7/0311/7/03

Keywords

  • Clouds
  • Constraint optimization
  • Databases
  • Hazardous materials
  • Monitoring
  • Motion detection
  • Object detection
  • Pollution
  • Prototypes
  • Tracking

ASJC Scopus subject areas

  • Software
  • Information Systems

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  • Cite this

    Hammad, M. A., Aref, W. G., & Elmagarmid, A. (2003). Stream window join: Tracking moving objects in sensor-network databases. In Proceedings of the International Conference on Scientific and Statistical Database Management, SSDBM (Vol. 2003-January, pp. 75-84). [1214967] IEEE Computer Society. https://doi.org/10.1109/SSDM.2003.1214967