Constraint-aware complex event pattern detection over streams

Ming Li, Murali Mani, Elke A. Rundensteiner, Tao Lin

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

3 Scopus citations

Abstract

In this paper, we propose a framework for constraint-aware pattern detection over event streams. Given the constraint of the input streams, our proposed framework on the fly checks the query satisfiability / unsatisfiability using a lightweight reasoning mechanism. Based on the constraint specified in the input stream, we are able to adjust the processing strategy dynamically, by producing early feedbacks, releasing unnecessary system resources and terminating corresponding pattern monitor, thus effectively decreasing the resource consumption and expediting the system response on certain situations. Our experimental study illustrates the significant performance improvement achieved by the constraint-aware pattern detection framework with little overhead.

Original languageEnglish (US)
Title of host publicationDatabase Systems for Advanced Applications - 15th International Conference, DASFAA 2010, Proceedings
Pages199-215
Number of pages17
EditionPART 2
DOIs
StatePublished - 2010
Externally publishedYes
Event15th International Conference on Database Systems for Advanced Applications, DASFAA 2010 - Tsukuba, Japan
Duration: Apr 1 2010Apr 4 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5982 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Database Systems for Advanced Applications, DASFAA 2010
Country/TerritoryJapan
CityTsukuba
Period4/1/104/4/10

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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