Distributed Architectures for Event-Based Systems

  • Valentin Cristea
  • Florin Pop
  • Ciprian Dobre
  • Alexandru Costan
Part of the Studies in Computational Intelligence book series (SCI, volume 347)


Event-driven distributed systems have two important characteristics, which differentiate them from other system types: the existence of several software or hardware components that run simultaneously on different inter-networked nodes, and the use of events as the main vehicle to organize component intercommunication. Clearly, both attributes influence event-driven distributed architectures, which are discussed in this chapter. We start with presenting the event-driven software architecture, which describes various logical components and their roles in events generation, transmission, processing, and consumption. This is used in early phases of distributed event-driven systems’ development as a blueprint for the whole development process including concept, design, implementation, testing, and maintenance. It also grounds important architectural concepts and highlights the challenges faced by event-driven distributed system developers. The core part of the chapter presents several system architectures, which capture the physical realization of event-driven distributed systems, more specifically the ways logical components are instantiated and placed on real machines. Important characteristics such as performance, efficient use of resources, fault tolerance, security, and others are strongly determined by the adopted system architecture and the technologies behind it. The most important research results are organized along five themes: complex event processing, Event-Driven Service Oriented Architecture (ED-SOA), Grid architecture, Peer-to-Peer (P2P) architecture, and Agent architecture. For each topic, we present previous work, describe the most recent achievements, highlight their advantages and limitations, and indicate future research trends in event-driven distributed system architectures.


Multiagent System Event Processing Composite Event Complex Event Processing Primitive Event 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Allen, J., Gerguson, G.: Action and Events in Interval Temporal Logic. Journal of Logic and Computation 4(5), 31–79 (1994)CrossRefGoogle Scholar
  2. 2.
    Ameur, R., Heudin, J.-C.: Interactive Intelligent Agent Architecture. In: Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IATW 2006), pp. 331–334. IEEE Computer Society, Washington (2006)CrossRefGoogle Scholar
  3. 3.
    Androutsellis-Theotokis, S., Spinellis, D.: A Survey of Peer-to-Peer Content Distribution Technologies. ACM Computing Surveys 36(4), 335–371 (2004)CrossRefGoogle Scholar
  4. 4.
    Anicic, D., Fodor, P., Stojanovic, N., Stühmer, R.: Computing complex events in an event-driven and logic-based approach. In: Proceedings of the Third ACM international Conference on Distributed Event-Based Systems (DEBS 2009), Nashville, Tennessee, USA, pp. 1–2 (2009)Google Scholar
  5. 5.
    Aydt, R., Smith, W., Swany, M., Taylor, V., Tierney, B., Wolski, R.: A Grid Monitoring Architecture. GWDPerf-16-3, Global Grid Forum (2001), (retrieved on February 02, 2010)
  6. 6.
    Baldoni, R., Beraldi, R., Quema, V., Querzoni, L., Tucci Piergiovanni, S.: A Scalable p2p Architecture for Topic-Based Event Dissemination. Technical report, Universita di Roma “La Sapienza” (2007)Google Scholar
  7. 7.
    Bank, D.: Web Services Eventing, W3C Member Submission (2006), (retrieved February 26, 2010)
  8. 8.
    Barella, A., Carrascosa, C., Botti, V.: Agent Architectures for Intelligent Virtual Environments. In: 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT 2007), pp. 532–535 (November 2007)Google Scholar
  9. 9.
    Barga, R.S., Goldstein, J., Ali, M., Hong, M.: Consistent Streaming Through Time: A Vision for Event Stream Processing. In: Proc. of the 3rd Biennial Conference on Innovative Data Systems Research (CIDR), Asilomar, California, USA, pp. 363–374 (2007)Google Scholar
  10. 10.
    Blanco, R., Wang, J., Alencar, P.: A metamodel for distributed event based systems. In: Proceedings of the Second international Conference on Distributed Event-Based Systems (DEBS 2008), vol. 332, pp. 221–232. ACM, New York (2008)CrossRefGoogle Scholar
  11. 11.
    Castro, M., Druschel, P., Kermarrec, A., Rowstron, A.: SCRIBE: A large-scale and decentralized application-level multicast infrastructure. IEEE JSAC 20(8), 1489–1499 (2002)Google Scholar
  12. 12.
    Chakravarthy, S., Adaikkalavan, R.: Provenance and Impact of Complex Event Processing (CEP): A Retrospective View. In: Buchmann, A., Koldehofe, B. (eds.) Special Issue of IT - Complex Event Processing, vol. 51(5), pp. 243–249. Oldenbourg Publications (September 2009)Google Scholar
  13. 13.
    Chakravarthy, S., Adaikkalavan, R.: Ubiquitous Nature of Event-Driven Approaches: A Retrospective View (Position Paper). In: Proceedings of the Dagstuhl Seminar 07191 (2007), (retreived January 10, 2010)
  14. 14.
    Chakravarthy, S., Mishra, D.: Snoop: An expressive event specification language for active databases. Data Knowledge Engineering 14(1), 1–26 (1994)CrossRefGoogle Scholar
  15. 15.
    Chakravarthy, S., Krishnaprasad, V., Anwar, E., Kim, S.-K.: Composite Events for Active Databases: Semantics, Contexts and Detection. In: Proceedings of the 20th International Conference on Very Large Data Bases, pp. 606–617. Morgan Kaufmann Publishers Inc., San Francisco (1994)Google Scholar
  16. 16.
    Chakravarty, P., Singh, M.P.: An event-driven approach for agent-based business process enactment. In: Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), Article No.: 214, Honolulu, Hawaii, pp. 1261–1263 (May 2007)Google Scholar
  17. 17.
    Chandrasekaran, S., Franklin, M.: Streaming queries over streaming data. In: Proc. of the 28th Int. Conference on Very Large Data Bases (VLDB 2002), pp. 203–214 (2002)Google Scholar
  18. 18.
    Cheng, S., Jih, W., Hsu, J.Y.: Context-aware Policy Matching in Event-driven Architecture. In: AAAI 2005 Workshop: Contexts and Ontologies: Theory, Practice and Applications, Pittsburgh, Pennsylvania, USA, pp. 140–141 (2005)Google Scholar
  19. 19.
    Cilia, M., Antollini, M., Bornovd, C., Buchman, A.: Dealing with heterogeneous data in pub/sub systems: The Concept-Based approach. In: International Workshop on Distributed Event-Based Systems (DEBS 2004), Edinburgh, Scotland (2004), (retrieved 10 January, 2010)
  20. 20.
    Cugola, G., Di Nitto, E., Fuggetta, A.: The jedi event-based infrastructure and its application to the development of the OPSS WFMS. IEEE Trans. Softw. Eng. 27(9), 827–850 (2001)CrossRefGoogle Scholar
  21. 21.
    Dasgupta, S., Bhat, S., Lee, Y.: Event Semantics for Service Composition in Pervasive Computing. In: Intelligent Event processing - AAAI Spring Symposium 2009, pp. 27–37. AAAI Press, Menlo Park (2009)Google Scholar
  22. 22.
    Doorenbos, R.B.: Production Matching for Large Learning Systems, PhD Thesis (1995), (retrieved March 11, 2010)
  23. 23.
    Ermagan, V., Krüger, I.H., Menarini, M.: Aspect-oriented modeling approach to define routing in enterprise service bus architectures. In: Proceedings of the 2008 International Workshop on Models in Software Engineering (MiSE 2008), Leipzig, Germany, pp. 15–20 (2008)Google Scholar
  24. 24.
    Etzion, O.: Event Cloud. Encyclopedia of Database Systems, 1034–1035 (2009)Google Scholar
  25. 25.
    Fortino, G., Garro, A., Mascillaro, S., Russo, W.: Using event-driven lightweight DSC-based agents for MAS modelling. International Journal on Agent Oriented Software Engineering (IJAOSE) 4(2), 113–140 (2010)CrossRefGoogle Scholar
  26. 26.
    Hinze, A., Michel, Y., Schlieder, T.: Approximative filtering of XML documents in a publish/subscribe system. In: 29th Australasian Computer Science Conference, ACSC 2006, pp. 177–185 (2006)Google Scholar
  27. 27.
    Hinze, A., Sachs, K., Buchmann, A.: Event-Based Applications and Enabling Technologies. In: Proc. of the 3rd ACM International Conference on Distributed Event-Based Systems (DEBS 2009), Nashville, TN, USA (2009), Session Keynote papers, Article No.: 1. (retrieved January 15, 2010)
  28. 28.
    Huang, Y., Gannon, D.: A Comparative Study of Web Services-based Event Notification Specifications. In: Proceedings of the 2006 international Conference Workshops on Parallel Processing (ICPPW), pp. 7–14. IEEE Computer Society, Washington (2006)CrossRefGoogle Scholar
  29. 29.
    IBM. IBM Tivoli Workload Scheduler Version 8.2: New Features and Best Practices. IBM Press (2004)Google Scholar
  30. 30.
    Jung, J., Park, J., Han, S., Lee, K.: An ECA-based framework for decentralized coordination of ubiquitous web services. Inf. Softw. Technol. 49(11-12), 1141–1161 (2007)CrossRefGoogle Scholar
  31. 31.
    Jung, J.-Y., Hong, Y.-S., Kim, T.-W., Park, J.: Human-Centered Event Description for Ubiquitous Service Computing. In: Proc. of International Conference on Multimedia and Ubiquitous Engineering, International Conference on Multimedia and Ubiquitous Engineering (MUE 2007), Seoul, Korea, pp. 1153–1157 (2007)Google Scholar
  32. 32.
    Khalifa, Y.M.A., Okoene, E., Al-Mourad, M.B.: Autonomous Intelligent Agent-Based Tracking Systems, Recent Developments. ICGST-ACSE Journal 7(1), 21–31 ( May 2007)Google Scholar
  33. 33.
    Kühn, E., Mordinyi, R., Keszthelyi, L., Schreiber, C., Bessler, S., Tomic, S.: Aspect-Oriented Space Containers for Efficient Publish/Subscribe Scenarios in Intelligent Transportation Systems. In: Meersman, R., Dillon, T., Herrero, P. (eds.) OTM 2009. LNCS, vol. 5870, pp. 432–448. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  34. 34.
    Lee, W.-s., Lee, S.-y., Lee, K.-c.: Conflict Detection and Resolution method in WS-ECA framework. In: Proc. of The 9th International Conference on Advanced Communication Technology, vol. 1, pp. 786–791 (2007)Google Scholar
  35. 35.
    Legrand, I.C., Cirstoiu, C., Grigoras, C., Betev, L., Costan, A.: Monitoring, accounting and automated decision support for the alice experiment based on the MonALISA framework. In: Proceedings of the 2007 Workshop on Grid Monitoring (GMW 2007), Monterey, California, USA, pp. 39–44 (2007)Google Scholar
  36. 36.
    Luckham, D.: The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems, May 18. Addison-Wesley Professional, Reading (2002)Google Scholar
  37. 37.
    Luckham, D., Schulte, R. (eds.): Event Processing Glossary - Version 1.1, Event Processing Technical Society (July 2008), (retrieved January 10, 2010)
  38. 38.
    Memon, A., Xie, Q.: Using Transient/Persistent Errors to Develop Automated Test Oracles for Event-Driven Software. In: Proceedings of the 19th IEEE international Conference on Automated Software Engineering. ASE, pp. 186–195. IEEE Computer Society, Washington (2004)CrossRefGoogle Scholar
  39. 39.
    Michelson, B.M.: Event-Driven Architecture Overview. Patricia Seybold Group / Business-Driven ArchitectureSM, February 2, pp. 1–8 (2006), (Retrieved January 10, 2010)
  40. 40.
    Mühl, G., Fiege, L., Pietzuch, P.: Distributed Event-Based Systems. Springer, Heidelberg (2006)zbMATHGoogle Scholar
  41. 41.
    Oliver, C.S.: Autonomous Mission Planning for a Distributed Surveillance System. Master Thesis: Department of Electrical and Computer Engineering. Carnegie Mellon University, USA (2000)Google Scholar
  42. 42.
    OMA. OMA Web Services Enabler (OWSER): Overview. OMA-AD-OWSER Overview-V1 1-20060328-A (2006), (retrieved March 20, 2010)
  43. 43.
    Paschke, A.: Design Patterns for Complex Event Processing. In: Proceedings of the 2nd International Conference on Distributed Event-Based Systems (DEBS 2008), Rome, Italy (2008), (retrieved Januaruy 15, 2010)
  44. 44.
    Pătrânjan, P.L.: The Language XChange: A Declarative Approach to Reactivity on the Web. PhD thesis. University of Munich, Germany (September 2005)Google Scholar
  45. 45.
    Pattberg, J., Fluegge, M.: Towards an ontology of collaboration patterns. Lecture Notes in Informatics, vol. 120 (2007), pp. 85–96 (2009), (retrieved February 1, 2010)
  46. 46.
    Rajasekar, A., Moore, R., Wan, M.: Event Processing in Policy Oriented Data Grids. In: Proc. of Intelligent Event Processing AAAI Spring Symposium, Stanford, California, USA, pp. 61–66 (2009)Google Scholar
  47. 47.
    Rosenblum, D., Wolf, A.: A design framework for internet-scale event observation and notification. ACM SIGSOFT Software Engineering Notes 22(6), 344–360 (1997)CrossRefGoogle Scholar
  48. 48.
    Saptharishi, M., Bhat, K., Diehl, C., Oliver, C., Savvides, M., Soto, A., Dolan, J., Khosla, P.: Recent Advances in Distributed Collaborative Surveillance. In: Proceedings of SPIE’s 14 Annual Conference on Aerospace-Defense Sensing, Simulation and Controls, AeroSense, Orlando, USA, pp. 129–208 (2000)Google Scholar
  49. 49.
    Schmidt, K.-U., Stühmer, R., Stojanovic, L.: Gaining Reactivity for Rich Internet Applications by Introducing Client-side Complex Event Processing and Declarative Rules. In: Proc. of the Intelligent Event Processing - AAAI Spring Symposium, pp. 67–72. Stanford University, USA (2009)Google Scholar
  50. 50.
    Schwiderski-Grosche, S., Moody, K.: The SpaTeC composite event language for spatio-temporal reasoning in mobile systems. In: Proceedings of the Third ACM international Conference on Distributed Event-Based Systems (DEBS 2009), Nashville, Tennessee, USA, pp. 1–12 (2009)Google Scholar
  51. 51.
    Seufert, A., Schiefer, J.: Enhanced Business Intelligence - Supporting Business Processes with Real-Time Business Analytics. In: Proceedings of the 16th International Workshop on Database and Expert Systems Applications (DEXA 2005), pp. 919–925 (2005)Google Scholar
  52. 52.
    Soh, L., Tsatsoulis, C.: Reflective Negotiating Agents for Real-Time Multisensor Target Tracking. International Journal Conference on Artificial Intelligence, 1121–1127 (2001)Google Scholar
  53. 53.
    Tanenbaum, A.S., van Steen, M.: Distributed Systems. Principles and paradigms, 2nd edn. Prentice-Hall, Englewood Cliffs (2007)zbMATHGoogle Scholar
  54. 54.
    Turchin, Y., Gal, A., Wasserkrug, S.: Tuning complex event processing rules using the prediction-correction paradigm. In: Proceedings of the Third ACM international Conference on Distributed Event-Based Systems (DEBS 2009), Nashville, Tennessee, USA, pp. 1–12 (2009)Google Scholar
  55. 55.
    Verginadis, Y., Apostolou, D., Papageorgiou, N., Mentzas, G.: Collaboration Patterns in event-driven environments for Virtual Organizations. In: Intelligent Event Processing - AAAI Spring Symposium 2009, Atlanta, US, pp. 92–97 (2009)Google Scholar
  56. 56.
    Vijayakumar, N., Plale, B.: Missing Event Prediction in Sensor Data Streams Using Kalman Filters. In: Ganguly, A.R., Gama, J., Omitaomu, O.A., Gaber, M.M., Vatsavai, R.R. (eds.) Knowledge Discovery From Sensor Data, pp. 149–170. CRC Press, Boca Raton (2009)Google Scholar
  57. 57.
    von Ammon, R., Emmersberger, C., Ertlmaier, T., Etzion, O., Paulus, T., Springer, F.: Existing and future standards for event-driven business process management. In: Gokhale, A., Schmidt, D.C. (eds.) Proceedings of the Third ACM International Conference on Distributed Event-Based Systems 2009, pp. 1–5. ACM, New York (2009)CrossRefGoogle Scholar
  58. 58.
    Xhafa, F., Paniagua, C., Barolli, L., Caballé, S.: A Parallel Grid-based Implementation for Real Time Processing of Event Log Data in Collaborative Applications. Int. J. Web and Grid Services, IJWGS 6(2) (2010) (in press)Google Scholar
  59. 59.
    Zaera, M.: Wave-based communication in vehicle to infrastructure real-time safety-related traffic telematics. Master’s thesis, Telecommunication Engineering. University of Zaragoza (August 2008)Google Scholar
  60. 60.
    Zhao, S., Stutzbach, D., Rejaie, R.: Characterizing files in the modern Gnutella network: A measurement study. In: Proc. Multi-media Computing and Networking Conf., San Jose, CA, USA, pp. 267–280 (2006)Google Scholar
  61. 61.
    Zhuang, S.Q., Zhao, B.Y., Joseph, A.D., Katz, R.H., Kubiatowicz, J.D.: Bayeux: an architecture for scalable and fault-tolerant wide-area data dissemination. In: Proc. of the 11th International Workshop on. Network and Operating Systems Support for Digital Audio and Video (NOSSDAV 2001), Danfords on the Sound, Port Jefferson, New York, USA, pp. 11–20 (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Valentin Cristea
    • 1
  • Florin Pop
    • 1
  • Ciprian Dobre
    • 1
  • Alexandru Costan
    • 1
  1. 1.University Politehnica of BucharestBucharestRomania

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