Analytical Patterns for Complex Event Processing

Back in March of 2006 during my enjoyable times at TIBCO Software, I presented a keynote at the first event processing symposium, Processing Patterns for Predictive Business.   In that presentation, I introduced a functional event processing reference architecture and highlighted the importance of mapping the business requirements for event processing to appropriate processing analytics and patterns.  The figure below is a screenshot of slide 26 of that presentation:

Slide 26

The idea behind the illustration above was that it is essential for organizations to look at their business problems and deterimine the best processing pattern, or processing analytics, in the context of the problem they are trying to solve.   I also graphically illustrated a few examples of event processing analytics relevant to CEP, including:

  • Rule-Based Inference;
  • Bayesian Belief Networks (Bayes Nets);
  • Dempster-Shafer’s Method;
  • Adaptive Neural Networks;
  • Cluster Analysis; and
  • State-Vector Estimation.

The key takeaway for that part of my presentation was that many analytics for CEP exist in the art & science of mature multi-sensor data fusion processing and these analytics can be mapped to recurring business patterns in event processing. I illustrated this point in slide 28 with the figure below (for illustrative purposes only):

Slide 26

In future posts on this topic I will elaborate by discussing analytics at each level of the functional CEP reference architecture, highlighting where different analytical methods and patterns can be efficiently applied to solve real-world event processing business problems.


One Response to Analytical Patterns for Complex Event Processing

  1. […] on distributed agents, or compare this commentary in the Wiki entry on the history of AI with these comments on what is needed in CEP… Filed in: AI, BPM, Complex Event Processing (CEP), Meetings and […]

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