Event Processing Reference Architecture Event Processing Reference Architecture Working Group March 24, 2006 Submitted by: Tim Bass, CISSP Principal Global Architect TIBCO Software Inc.

Event Processing Reference Architecture 24 EVENT PRE-PROCESSING EVENT SOURCES EXTERNAL . . . LEVEL ONE EVENT REFINEMENT USER INTERFACE Event Processing (EP/CEP) DB MANAGEMENT Historical Data Profiles & Patterns DISTRIBUTED LOCAL EVENT SERVICES . . EVENT PROFILES . . DATA BASES . . OTHER DATA LEVEL TWO SITUATION REFINEMENT LEVEL THREE IMPACT ASSESSMENT LEVEL FOUR PROCESS REFINEMENT Adapted from JDL: Steinberg, A., & Bowman, C., Handbook of Multisensor Data Fusion, CRC Press, 2001

Summary of Event Processing (Event-Decision) User Interface Human visualization, interaction and situation management Level 4 - Process Refinement Decide on control feedback, for example resource allocation, event source and state management, parametric and algorithmic adjustments Level 3 - Impact Assessment Impact assessment, i.e. assess impact on the basis of situation development, recognition and prediction Level 2 – Situation Refinement Identify situations based on events relations, relational state estimation, etc. Level 1 – Event Refinement Identify and track events based on association, filtering, joins, correlation etc. Level 0 – Event Preprocessing Cleansing of event-stream to produce semantically understandable data Event Sources Level of Inference Low Med High Reference: Bass, T., Processing Patterns for PredictiveBusiness™, March 2006.

User Interface

Human visualization, interaction and situation management

Level 4 - Process Refinement

Decide on control feedback, for example resource allocation, event source and state management, parametric and algorithmic adjustments

Level 3 - Impact Assessment

Impact assessment, i.e. assess impact on the basis of situation development, recognition and prediction

Level 2 – Situation Refinement

Identify situations based on events relations, relational state estimation, etc.

Level 1 – Event Refinement

Identify and track events based on association, filtering, joins, correlation etc.

Level 0 – Event Preprocessing

Cleansing of event-stream to produce semantically understandable data

Event Sources

A Handful of References Ranadiv é , V., The Power to Predict , McGraw-Hill, 2006. Bass, T., Processing Patterns for PredictiveBusiness™ , Event Processing Symposium, Hawthorne, NY, March 2006. Luckham, D., The Power of Events , Addison-Wesley, NY, 2002. Hall, D. and Llinas, J., Handbook of Multisensor Data Fusion , CRC Press, New York, 2001. Bass, T., Intrusion Detection Systems & Multisensor Data Fusion, Communications of the ACM, pp. 99-105, Vol. 43, No. 4, April 2000.

Ranadiv é , V., The Power to Predict , McGraw-Hill, 2006.

Bass, T., Processing Patterns for PredictiveBusiness™ , Event Processing Symposium, Hawthorne, NY, March 2006.

Luckham, D., The Power of Events , Addison-Wesley, NY, 2002.

Hall, D. and Llinas, J., Handbook of Multisensor Data Fusion , CRC Press, New York, 2001.

Bass, T., Intrusion Detection Systems & Multisensor Data Fusion, Communications of the ACM, pp. 99-105, Vol. 43, No. 4, April 2000.