Complex Event Processing using Simple Rule-based Event Correlation Engines for Business Performance Management

Authors:
Shyh-Kwei Chen;Jun-Jang Jeng;Henry Chang
Affiliations:
IBM T.J. Watson Research Center;IBM T.J. Watson Research Center;IBM T.J. Watson Research Center
Venue:
CEC-EEE '06 Proceedings of the The 8th IEEE International Conference on E-Commerce Technology and The 3rd IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services
Year:
2006

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Abstract

Event correlation is an important component in business performance management. Simple rule-based event correlation engines, like Zurich Correlation Engine (ZCE), usually accept input events that include only name-value pairs. However, when input events are in XML format, the ZCE needs to be adapted to accept complex/structural events. In this paper, we present a model-driven approach to derive solutions for adapting the new type of events, so that the light weight correlation engine can still be used for event monitoring and correlation.