Event-Driven Virtual Machine for Business Integration Middleware

  • Joachim H. Frank
  • Liangzhao Zeng
  • Henry Chang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6470)


Business integration middleware uses a variety of programming models to enable business process automation, business activity monitoring, business object state management, service mediation, etc. Different kinds of engines have been developed in support of these programming models. At their core however, all of these engines implement the same kind of behavior: formatted messages (or events) are received, processed in the context of managed objects, and new messages are emitted. These messages can represent service invocations and responses, tracking events, notifications, or point-to-point messages between applications. The managed objects can represent process instances, state machines, monitors, or service mediations. Developing separate engines for each programming model results in redundant implementation efforts, and may even cause an "integration problem" for the integration middleware itself. To address these issues, we propose to use an event-driven virtual machine that implements the fundamental behavior of all business integration middleware as the sole execution platform, and provide compilers for higher level programming models. Conceptually, this is similar to passing from CISC to RISC architecture in CPU design: efficiently implement a small instruction set, and support higher level languages via compilers.


  1. 1.
    Zeng, L., Lei, H., Chang, H.: Model-analysis for Business Event Processing. IBM Systems journal (2007)Google Scholar
  2. 2.
    Zeng, L., Lei, H., Dikun, M.J., Chang, H., Bhaskaran, K.: Model-Driven Business Performance Management. In: ICEBE 2005, pp. 295–304 (2005)Google Scholar
  3. 3.
  4. 4.
    SOAP specification,
  5. 5.
  6. 6.
  7. 7.
  8. 8.
    Apache Cassandra,
  9. 9.
    Kulkarni, K., Mattos, N.M., Cochrane, R.: Active database features in SQL3. In: Paton, N.W., Gries, D., Schneider, F. (eds.) Active rules in database systems. Monographs in computer science, pp. 197–219. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  10. 10.
    Babu, S., Widom, J.: Continuous queries over data streams. In: SIGMOD Rec. 30,3,2Google Scholar
  11. 11.
    Fjording the Stream: An Architecture for Queries over Streaming Sensor Data. In: ICDE 2002 (2002)Google Scholar
  12. 12.
    Chandrasekaran, S., Franklin, M.J.: Streaming Queries over Streaming Data. In: VLDB 2002 (2002)Google Scholar
  13. 13.
    Luckham, D.C.: The Power of Events: an Introduction to Complex Event Proc-essing, in Distributed Enterprise Systems. Addison-Wesley Longman, Inc, AmsterdamGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Joachim H. Frank
    • 1
  • Liangzhao Zeng
    • 2
  • Henry Chang
    • 2
  1. 1.IBM Software GroupUSA
  2. 2.IBM T.J. Watson Research CenterUSA

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