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Keynote at Depsa07 - architectural view of event processing
 

Keynote at Depsa07 - architectural view of event processing

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    Keynote at Depsa07 - architectural view of event processing Keynote at Depsa07 - architectural view of event processing Presentation Transcript

    • IBM Software Group – Event Processing technologies ! quot; ! # $ © 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
    • 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 !quot; 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
    • IBM Software Group – Event Processing Technologies and Architecture $ !% 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 #
    • 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 ( ) * ) + ( , -. - * .* / 01 2( 3 $ quot; 2 + , - ,4 5 ( 6 ) 78 + ) 6 - ,9 6 6 9 7 quot; $ ! 8 7 ': 6 ' * ,9 / 1 2( 6( % +/ 6! 8 76 ' ; ' $ ,9 / *( , $ / 6 < 7 ': 6 '; Event-Driven Processing in IBM © 2007 IBM Corporation &&
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    • IBM Software Group – Event Processing Technologies and Architecture Processor examples: ! 7 +! Validate, transform, detect pattern, derive, enrich Selector Processor Router Event-Driven Processing in IBM © 2007 IBM Corporation &
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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
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