Complex event processing using simple rule-based event correlation engines for business performance management

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. © 2006 IEEE.