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CEP: Event-Decision Architecture for  PredictiveBusiness TM Centre for Strategic Infocomm Technologies (CSIT), Singapore July 26, 2006  Tim Bass, CISSP  Principal Global Architect, Director  TIBCO Software Inc.
Our Agenda ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
A Vocabulary of Confusion  (Work in Progress) Resource Management Data Fusion Sensor Fusion Information Fusion Tracking Data Mining Correlation Planning Complex Event Processing Processing Management Sensor Management Control Estimation Event Stream Processing Adapted from:  Steinberg, A., & Bowman, C.,  CRC Press,  2001
PredictiveBusiness TM
Example PredictiveBusiness TM  Scenarios ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
PredictiveBusiness TM  & Complex Event Processing (CEP) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]," Events in several forms, from simple events to complex events, will become very widely used in business applications during 2004 through 2008 "  --- Gartner July 2003 Graphic Sources:  TIBCO Software Inc & IBM CEP Situation Manager Event Streams Historical Data Real-time Detection  and Prediction
Our Agenda ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Overview of IT and Decision Making What is a High Level View of How Businesses Make Decisions? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Document- Driven ,[object Object],[object Object],[object Object],[object Object],Knowledge- Driven Decision Making Communications- Driven Model- Driven Data- Driven
TIBCO BusinessEvents™ Solutions Overview BusinessEvents™ Solutions Space Data: Events & Databases -Real-Time & Historical Data Models: Statistical Financial Optimization Comms: Pub/Sub Messaging Queues Topics UIs Knowledge: Facts & Rules
A Business Optimization Perspective What Classes of Rule-Based Problems Do Businesses Need to Solve? Rule-Based ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Detection Prediction Scheduling ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Solving a Broad Class of Complex Problems
Event-Decision Hierarchy 22 Impact Assessment Situational Assessment Relationship of Events Identify Events Location, Times and Rates of Events of Interest Existence of Possible Event of Interest Data/Event Cloud Analysis of Situation & Plans Contextual and Causal  Analysis Causal Analysis, Bayesian Belief Networks, NNs, Correlation, State Estimation, Classification Use of Distributed Sensors for Estimations Raw Sensor Data (Passive and Active) Adapted from: Waltz, E. & Llinas, J., Multisensor Data Fusion, 1990 HIGH LOW MED
Event-Decision High Level Architecture 22 EVENT CLOUD (DISTRIBUTED DATA SET) KS KS KS KS KS KS KS KS KS KS KS KS KS KS Adapted from:  Engelmore, R. S., Morgan, A.J., & and Nii, H. P., Blackboard Systems, 1988 & Luckham, D., The Power of Events, 2002
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],HLA - Knowledge Sources KS KS KS
Event-Decision Reference Architecture 24 EVENT PRE-PROCESSING EVENT SOURCES EXTERNAL .  .  .  LEVEL ONE EVENT REFINEMENT USER INTERFACE COMPLEX EVENT PROCESSING (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
Structured Processing for Event-Decision ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Level of  Inference Low Med High
CEP Level 0 –  Event Preprocessing  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
CEP Level 1 – Event Refinement  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
CEP Level 2 – Situation Refinement ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
CEP Level 3 – Impact Assessment ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
CEP Level 4 – Process Refinement  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
CEP - Database Management Examples ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
CEP Level 5 – User Interface / Interaction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
TIBCO’S Event-Decision Reference Architecture Flexible SOA and Event-Driven Architecture
Our Agenda ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Event Processing Application Scenarios  Examples of Detection-Prediction Scenarios We Solve for Customers POC Fraud Detection Financial Services Pre-Sales Intrusion Detection Financial Services Production Supply Chain Monitoring Business Hub  (B2B) Planning/POC Supply Chain Monitoring Manufacturing Pre-Sales Anti Money Laundering Government Pre-Sales Power Grid Monitoring Energy Production Track & Trace Transportation Production Service Monitoring Telecommunications Pre-Sales Track & Trace Supply Chain - Logistics Pre-Sales Network & Applications Management Telecommunications Status (2Q06) Application  Scenarios Industry
Identity Theft Detection / Phishing Example Fraud Detection Scenario   Source:  Bass, T., TIBCO Software Inc., January 2006 Uses Proxy Alert Service Account Lockout Profile Mismatch Brand Phishing Alert Security Alert Customer Known Fraud IP Identity Theft Login Success Phishing Alert Brand Misuse
Customer Case Study: Fusion-Based IDS High Level Event-Driven Architecture (EDA) – Early Phase JAVA  MESSAGING SERVICE  (JMS) DISTRIBUTED QUEUES (TIBCO EMS) HIGH PERFORMANCE RULES-ENGINE (TIBCO BE) HIGH PERFORMANCE RULES-ENGINE (TIBCO BE) HIGH PERFORMANCE RULES-ENGINE (TIBCO BE) HIGH PERFORMANCE RULES-ENGINE (TIBCO BE ) SENSOR NETWORK RULES NETWORK NIDS BW JMS LOGFILE JMS BW LOGFILE JMS BW LOGFILE JMS BW IDS JMS BW HIDS JMS BW SQL DB BW JMS ADB SQL DB BW JMS ADB MESSAGING NETWORK TIBCO PRODUCTS
Overview of Mizuho Securities Solutions Architecture ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Potential Extensions to Solutions Architecture ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Event-Decision Processing Characteristics Adapted (this and the next slide) from:  Steinberg, A., & Bowman, C.,  Handbook of Multisensor Data Fusion, CRC Press,  2001 Sensor Output Individual Event Aggregation  (situation) Effect  (situation, given plan) (Action) Entity  Estimate Sensor Processing Event  Processing Situation Assessment Impact  Assessment Decision  Making Activity Detection Assignment (L0)  Event Preprocessing Attribution Assignment (L1)  Event Refinement Relational Aggregation (L2)  Situation Refinement Plan  Interaction Aggregation (L3)  Impact  Assessment (Control) Planning (L4)  Process Refinement Estimation Process Association Process JDL Model  Levels
Comparison of Event-Decision Models Sense Detect Detect Analyze Analyze Decide Respond Sense & Respond Sensor Processing Collate Orient Sensor Processing (L0)  Event Preprocessing Sensor Acquisition Collect Observe Sensing --- Activity Intelligence  Cycle Boyd  Loop Waterfall  Model JDL Model  Levels Decision Execution Disseminate Act (L5)  Visualization Collate Evaluate Evaluate Disseminate Event  Processing Situation Assessment Impact  Assessment Decision  Making Orient Pattern Processing / Feature Extraction (L1)  Event Refinement Orient Situation Assessment (L2)  Situation Refinement Orient --- (L3)  Impact  Assessment Decide Decision  Making (L4)  Process Refinement
Enterprise Scenario The Full Range of Business Integration Products and Services EVENTS EVENTS
Key Takeaways ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Thank You! Tim Bass, CISSP Principal Global Architect [email_address] Complex Event Processing at TIBCO
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CEP: Event-Decision Architecture for PredictiveBusiness, July 2006

  • 1. CEP: Event-Decision Architecture for PredictiveBusiness TM Centre for Strategic Infocomm Technologies (CSIT), Singapore July 26, 2006 Tim Bass, CISSP Principal Global Architect, Director TIBCO Software Inc.
  • 2.
  • 3.
  • 4. A Vocabulary of Confusion (Work in Progress) Resource Management Data Fusion Sensor Fusion Information Fusion Tracking Data Mining Correlation Planning Complex Event Processing Processing Management Sensor Management Control Estimation Event Stream Processing Adapted from: Steinberg, A., & Bowman, C., CRC Press, 2001
  • 6.
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  • 10. TIBCO BusinessEvents™ Solutions Overview BusinessEvents™ Solutions Space Data: Events & Databases -Real-Time & Historical Data Models: Statistical Financial Optimization Comms: Pub/Sub Messaging Queues Topics UIs Knowledge: Facts & Rules
  • 11.
  • 12. Event-Decision Hierarchy 22 Impact Assessment Situational Assessment Relationship of Events Identify Events Location, Times and Rates of Events of Interest Existence of Possible Event of Interest Data/Event Cloud Analysis of Situation & Plans Contextual and Causal Analysis Causal Analysis, Bayesian Belief Networks, NNs, Correlation, State Estimation, Classification Use of Distributed Sensors for Estimations Raw Sensor Data (Passive and Active) Adapted from: Waltz, E. & Llinas, J., Multisensor Data Fusion, 1990 HIGH LOW MED
  • 13. Event-Decision High Level Architecture 22 EVENT CLOUD (DISTRIBUTED DATA SET) KS KS KS KS KS KS KS KS KS KS KS KS KS KS Adapted from: Engelmore, R. S., Morgan, A.J., & and Nii, H. P., Blackboard Systems, 1988 & Luckham, D., The Power of Events, 2002
  • 14.
  • 15. Event-Decision Reference Architecture 24 EVENT PRE-PROCESSING EVENT SOURCES EXTERNAL . . . LEVEL ONE EVENT REFINEMENT USER INTERFACE COMPLEX EVENT PROCESSING (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
  • 16.
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  • 23.
  • 24. TIBCO’S Event-Decision Reference Architecture Flexible SOA and Event-Driven Architecture
  • 25.
  • 26. Event Processing Application Scenarios Examples of Detection-Prediction Scenarios We Solve for Customers POC Fraud Detection Financial Services Pre-Sales Intrusion Detection Financial Services Production Supply Chain Monitoring Business Hub (B2B) Planning/POC Supply Chain Monitoring Manufacturing Pre-Sales Anti Money Laundering Government Pre-Sales Power Grid Monitoring Energy Production Track & Trace Transportation Production Service Monitoring Telecommunications Pre-Sales Track & Trace Supply Chain - Logistics Pre-Sales Network & Applications Management Telecommunications Status (2Q06) Application Scenarios Industry
  • 27. Identity Theft Detection / Phishing Example Fraud Detection Scenario Source: Bass, T., TIBCO Software Inc., January 2006 Uses Proxy Alert Service Account Lockout Profile Mismatch Brand Phishing Alert Security Alert Customer Known Fraud IP Identity Theft Login Success Phishing Alert Brand Misuse
  • 28. Customer Case Study: Fusion-Based IDS High Level Event-Driven Architecture (EDA) – Early Phase JAVA MESSAGING SERVICE (JMS) DISTRIBUTED QUEUES (TIBCO EMS) HIGH PERFORMANCE RULES-ENGINE (TIBCO BE) HIGH PERFORMANCE RULES-ENGINE (TIBCO BE) HIGH PERFORMANCE RULES-ENGINE (TIBCO BE) HIGH PERFORMANCE RULES-ENGINE (TIBCO BE ) SENSOR NETWORK RULES NETWORK NIDS BW JMS LOGFILE JMS BW LOGFILE JMS BW LOGFILE JMS BW IDS JMS BW HIDS JMS BW SQL DB BW JMS ADB SQL DB BW JMS ADB MESSAGING NETWORK TIBCO PRODUCTS
  • 29.
  • 30.
  • 31. Event-Decision Processing Characteristics Adapted (this and the next slide) from: Steinberg, A., & Bowman, C., Handbook of Multisensor Data Fusion, CRC Press, 2001 Sensor Output Individual Event Aggregation (situation) Effect (situation, given plan) (Action) Entity Estimate Sensor Processing Event Processing Situation Assessment Impact Assessment Decision Making Activity Detection Assignment (L0) Event Preprocessing Attribution Assignment (L1) Event Refinement Relational Aggregation (L2) Situation Refinement Plan Interaction Aggregation (L3) Impact Assessment (Control) Planning (L4) Process Refinement Estimation Process Association Process JDL Model Levels
  • 32. Comparison of Event-Decision Models Sense Detect Detect Analyze Analyze Decide Respond Sense & Respond Sensor Processing Collate Orient Sensor Processing (L0) Event Preprocessing Sensor Acquisition Collect Observe Sensing --- Activity Intelligence Cycle Boyd Loop Waterfall Model JDL Model Levels Decision Execution Disseminate Act (L5) Visualization Collate Evaluate Evaluate Disseminate Event Processing Situation Assessment Impact Assessment Decision Making Orient Pattern Processing / Feature Extraction (L1) Event Refinement Orient Situation Assessment (L2) Situation Refinement Orient --- (L3) Impact Assessment Decide Decision Making (L4) Process Refinement
  • 33. Enterprise Scenario The Full Range of Business Integration Products and Services EVENTS EVENTS
  • 34.
  • 35. Thank You! Tim Bass, CISSP Principal Global Architect [email_address] Complex Event Processing at TIBCO