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A middleware platform_to_federate_complex_event_processing

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A Middleware Platform to Federate
ComplexEvent Processing

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A middleware platform_to_federate_complex_event_processing

  1. 1. A Middleware Platform to Federate Complex Event Processing Fawaz Paraïso, Gabriel Hermosillo, Romain Rouvoy, Philippe Merle, Lionel Seinturier The Sixteenth IEEE International EDOC Conference (2012) University of Lille & Inria lille-Nord Europe (France) 1
  2. 2. Agenda• Motivation• Challenges• Contribution• Validation• Conclusion & Perspectives 2
  3. 3. Motivation• What do we mean by event? – A piece of data that represents something happened in the real world• Event-driven behaviour in daily life – Computer – Systems –… 3
  4. 4. Motivation• Events are everywhere Produce events 4
  5. 5. Motivation• Events are useless if they are not filtered and correlated ProcessingEvents 5
  6. 6. Motivation• What is Complex Event Processing (CEP)? – Real time processing – Intelligent business applications• What applications can benefit from CEP? – Real-time supply chain management – Algorithm trading – Monitoring (transaction, network, …) – Credit card fraud detection 6
  7. 7. Motivation• The need for real-time processing of information is relevant for many systems – Business activity monitoring – Fraud detection – Nuclear crisis management 7
  8. 8. National Motivation Radiation Survey NetworkWeatherForecast Experts Police Firemen Population Media Nuclear Central Emergency Army Medical Service Operation Decision Local authority 8
  9. 9. Agenda• Motivation• Challenges• Contribution• Validation• Conclusion & Perspectives 9
  10. 10. Challenges• Challenge 1: Communication heterogeneity 10
  11. 11. Challenges• Challenge 2: Heterogeneous CEP Engines StreamCruncher Esper Etalis CEP ruleCore Server 11
  12. 12. Challenges• Challenge 3: Scalability Performance & Scalability 12
  13. 13. Challenges• Challenge 4: Adaptability 13
  14. 14. Agenda• Motivation• Challenges• Contribution• Validation• Conclusion & Perspectives 14
  15. 15. Contribution• A Middleware Platform to Federate Complex Event Processing – Federate distributed CEP Engines – Supports multiple communication services REST, JMS, WS-Notification – The DiCEPE Platform is an SCA-based solution – Implemented in SCA using FraSCAti Reflective component model Runtime adaptative system 15
  16. 16. Contribution• Distributed Platform Architecture DiCEPE DiCEPE DiCEPE 16
  17. 17. Contribution• Platform Architecture * ListenerBinding Rest *Binding Engine Statement JMS Context DiCEPE Legend Composite Component Service Reference Property Wire 17
  18. 18. Contribution• Platform Architecture – Communication heterogeneity Orchestrate heterogenenous services Different bindings REST, WS, JMS, JNA, UPnP, RPC ,RMI, JGroups, etc. – Reconfiguration capability Dynamic reconfigurable runtime architecture 18
  19. 19. Contribution• Platform architecture – Facililate the integration of CEP engine Compose an heterogenous piece of software to build a new service Supports various Implementation technologies (Java, BPEL, C, C++, Python, …) Interface definiton language (WSDL, Java) 19
  20. 20. Contribution• The Platform adresses the challenges of : – Communication heterogeneity – Heterogeneous CEP – Scalability – Adaptability 20
  21. 21. Agenda• Motivation• Challenges• Contribution• Validation• Conclusion & Perspectives 21
  22. 22. Validation• DiCEPE for nuclear crisis management Available here: http://dicepe-broker.soceda.cloudbees.net 22
  23. 23. Validation• The SCA validates the challenge: – Communication heterogeneity – Heterogeneous CEP – Scalability – Adaptability 23
  24. 24. Validation• Integration with the Esper and Etalis engine Input 1 Events EventExecutionWorker 1 2 EsperServiceProvider Configuration 3 EPL 4 4 Event object statement 2 Statements PrologEngineWrapper Listeners 5 3 Etalis Output EtalisEventListener Prolog EventsOverview of Esper Engine Architecture EtalisWrapper 5 3 4 DiCEPE 4 Architecture 1 2 3 1 2 24
  25. 25. Validation• The integration of Esper and Etalis CEP engine validates the challenge : – Communication heterogeneity – Heterogeneous CEP – Scalability – Adaptability 25
  26. 26. Validation• DiCEPE Cost Analysis Implementation Avg. Exec. Time SCA overhead Esper 27 sec - DiCEPE (Esper+ FraSCAti) 30 sec 11% 26
  27. 27. Validation• DiCEPE Scalability Firemen Events Failures Avg. Sessions Avg. response 10,000 500,000 0 89 0.113 ms 15,000 750,000 0 135 0.142 ms + 50% + 50% - + 51% + 26% 27
  28. 28. Validation• The scalability analysis validates the challenge – Communication heterogeneity – Heterogeneous CEP – Scalability – Adaptability 28
  29. 29. Validation• Dynamic reconfiguration 29
  30. 30. Validation• The FraSCAti validates the challenge: – Communication heterogeneity – Heterogeneous CEP – Scalability – Adaptability 30
  31. 31. Agenda• Motivation• Challenges• Contribution• Validation• Conclusion & Perspectives 31
  32. 32. Conclusion & Perspectives• DiCEPE offers interoperability between CEP engines via federation• Flexible component architecture – Successful integration and validation of CEP engines – Multiple communication protocols• Real scalability• Integrate a Domain Specific Language(DSL) to express rules• Deployment of DiCEPE on heterogeneous cloud environments• Error handling capabilities for distributed environments 32
  33. 33. Thank you Questions?@email: fawaz.paraiso@inria.fr 33

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