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IBM Software Group – Event Processing Technologies and Architecture
Event Processing in a nutshell
Event Processing Network – as main
abstraction
Architectural Principles
Producing and consuming the events
Processing the events
Some Non-Functional Issues
Concluding Remarks
Event-Driven Processing in IBM © 2007 IBM Corporation

IBM Software Group – Event Processing Technologies and Architecture
Event Processing in a nutshell
Event Processing Network – as main
abstraction
Architectural Principles
Producing and consuming the events
Processing the events
Some Non-Functional Issues
Concluding Remarks
Event-Driven Processing in IBM © 2007 IBM Corporation

Event Processing
Event Event
Producer Consumer
Generate and Consume and
may publish perform operations react to either
events on events raw or complex
events
!

EDA Reference Architecture Overview
Event Event Business State
Services
Producer Sensors Processes Machines
Event Monitoring and Analytic Infrastructure
Event Consolidator
Event Security Services
Event Flow
Event
Event Bus
Processing
Network
Event Operator (Facilitator)
Event Event Business State
Services
Consumer Actuators Processes Machines
© 2003 IBM Corporation 5

IBM Software Group – Event Processing Technologies and Architecture
Consumers
Producers Agents
g
Event-Driven Processing in IBM © 2007 IBM Corporation

IBM Software Group – Event Processing Technologies and Architecture
Consumers
Producers Agents
Transform validate
g
Retrospective pattern
if the customer has breached his credit limit the second time within the last 48
hours then divert the workflow based on policies that relate to the history of
credit violations in the last year.
Event-Driven Processing in IBM © 2007 IBM Corporation

IBM Software Group – Event Processing Technologies and Architecture
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Consumers
Producers Agents
Detect Pattern
Enrich
g
If a customer sends three requests over the last hour on the same topic and
the requests have been handled, notify immediately to the “unhappy
customers officer” and include count of “unhappy” detections for this customer
in the last year
Event-Driven Processing in IBM © 2007 IBM Corporation

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Consumers
Producers Agents
Detect Pattern
Dynamic
Subscribe
g
I am interested to know whenever my investment portfolio is down 2 percent
within the last couple of hours
Event-Driven Processing in IBM © 2007 IBM Corporation
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IBM Software Group – Event Processing Technologies and Architecture
Event Processing in a nutshell
Event Processing Network – as main
abstraction
Architectural Principles
Producing and consuming the events
Processing the events
Some Non-Functional Issues
Concluding Remarks
Event-Driven Processing in IBM © 2007 IBM Corporation
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Processor examples:
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Validate, transform, detect
pattern, derive, enrich
Selector Processor Router
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Event Processing Reference Architecture
EVENT
SOURCES
EVENT PRE- Event Processing (EP/CEP)
EXTERNAL PROCESSING
DISTRIBUTED
LEVEL ONE LEVEL TWO LEVEL THREE
LOCAL
EVENT SITUATION IMPACT
EVENT REFINEMENT REFINEMENT ASSESSMENT
SERVICES
.
. USER
EVENT
. INTERFACE
PROFILES
.
. .
.
DB MANAGEMENT
DATA
BASES
. Historical Profiles &
LEVEL FOUR Data Patterns
.
OTHER
PROCESS
DATA
REFINEMENT
Adapted from JDL:
Steinberg, A., & Bowman, C., Handbook of Multisensor Data Fusion, CRC Press, 2001
21 © 2006 TIBCO Software Inc. All Rights Reserved. Confidential and Proprietary. 24

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 of Level 3 - Impact Assessment
Inference Impact assessment, i.e. assess impact on the basis of situation development, recognition
and prediction
Level 2 – Situation Refinement
High 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.
Med Level 0 – Event Preprocessing
Cleansing of event-stream to produce semantically understandable data
Event Sources
Low
Reference: Bass, T., Processing Patterns for PredictiveBusiness™, March 2006.
22 © 2006 TIBCO Software Inc. All Rights Reserved. Confidential and Proprietary.

Overview
Event Data
publish Processing consume
Publication Consumption
(Publishers) Selection (Consumers*)
Correlation
Distribution
Applications Files/DBs Sensor Data Feeds Propagations
* Consumers can act as publishers
23

Event Data Processing
Event Data
Processing
Stream
Stream Select
Process
Compose Stream
Retain
Deliver/propagate
Stream Stream
Single or multiple steps
Local or distributed
24

IBM Software Group – Event Processing Technologies and Architecture
Event Processing in a nutshell
Event Processing Network – as main
abstraction
Architectural Principles
Producing and consuming the events
Processing the events
Some Non-Functional Issues
Concluding Remarks
Event-Driven Processing in IBM © 2007 IBM Corporation
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IBM Software Group – Event Processing Technologies and Architecture
Event Processing in a nutshell
Event Processing Network – as main
abstraction
Architectural Principles
Producing and consuming the events
Processing the events
Some Non-Functional Issues
Concluding Remarks
Event-Driven Processing in IBM © 2007 IBM Corporation

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Event Processing in a nutshell
Event Processing Network – as main
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Architectural Principles
Producing and consuming the events
Processing the events
Some Non-Functional Issues
Concluding Remarks
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Event Processing in a nutshell
Event Processing Network – as main
abstraction
Architectural Principles
Producing and consuming the events
Processing the events
Some Non-Functional Issues
Concluding Remarks
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Event Processing in a nutshell
Event Processing Network – as main
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Architectural Principles
Producing and consuming the events
Processing the events
Some Non-Functional Issues
Concluding Remarks
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