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    Event composition and detection in data stream management systems

    Access Status
    Fulltext not available
    Authors
    Mohania, M.
    Dhruv, S.
    Gupta, S.
    Bhowmick, S.
    Dillon, Tharam S.
    Date
    2005
    Type
    Conference Paper
    
    Metadata
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    Citation
    Mohania, M. and Dhruv, S. and Gupta, S. and Bhowmick, S. and Dillon, T.S. 2005. Event composition and detection in data stream management systems, in Kim Viborg Andersen, John Debenham and Roland Wagner (ed), 16th International Conference on Database and Expert Systems Applications (DEXA 2005), Aug 22 2005, pp. 756-765. Copenhagen, Denmark: Springer.
    Source Title
    Database and Expert Systems Applications
    Source Conference
    16th International Conference on Database and Expert Systems Applications (DEXA 2005)
    DOI
    10.1007/11546924_74
    ISBN
    9783540285663
    URI
    http://hdl.handle.net/20.500.11937/45362
    Collection
    • Curtin Research Publications
    Abstract

    There has been a rising need to handle and process streaming kind of data. It is continuous, unpredictable, time-varying in nature and could arrive in multiple rapid streams. Sensor data, web clickstreams, etc. are the examples of streaming data. One of the important issues about streaming data management systems is that it needs to be processed in real-time. That is, active rules can be defined over data streams for making the system reactive. These rules are triggered based on the events detected on the data stream, or events detected while summarizing the data or combination of both. In this paper, we study the challenges involved in monitoring events in a Data Stream Management System (DSMS) and how they differ from the same in active databases. We propose an architecture for event composition and detection in a DSMS, and then discuss an algorithm for detecting composite events defined on both the summarized data streams and the streaming data.

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