Complex event pattern detection over streams with interval-based temporal semantics

  • Authors:
  • Ming Li;Murali Mani;Elke A. Rundensteiner;Tao Lin

  • Affiliations:
  • IBM Corporation, San Jose, CA, USA;University of Michigan-Flint, Flint, MI, USA;Worcester Polytechnic Institute, Worcester, MA, USA;Amitive, Redwood City, CA, USA

  • Venue:
  • Proceedings of the 5th ACM international conference on Distributed event-based system
  • Year:
  • 2011

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Abstract

In this work, we study the event pattern matching mechanism over streams with interval-based temporal semantics. An expressive language to represent the required temporal patterns among streaming interval events is introduced and the corresponding temporal operator ISEQ is designed. For further improving the interval event processing performance, a punctuation-aware stream processing strategy is provided. Experimental studies illustrate that the proposed techniques bring significant performance improvement in both memory and CPU usage with little overhead.