Event-Based Monitoring of Process Execution Violations

  • Matthias Weidlich
  • Holger Ziekow
  • Jan Mendling
  • Oliver Günther
  • Mathias Weske
  • Nirmit Desai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6896)


Process-aware information systems support business operations as they are typically defined in a normative process model. Often these systems do not directly execute the process model, but provide the flexibility to deviate from the normative model. This paper proposes a method for monitoring control-flow deviations during process execution. Our contribution is a formal technique to derive monitoring queries from a process model, such that they can be directly used in a complex event processing environment. Furthermore, we also introduce an approach to filter and aggregate query results to provide compact feedback on deviations. Our techniques is applied in a case study within the IT service industry.


Business Process Constraint Violation Process Instance Complex Event Processing Event Query 
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.
    Dumas, M., ter Hofstede, A., van der Aalst, W. (eds.): Process Aware Information Systems: Bridging People and Software Through Process Technology. Wiley Publishing, Chichester (2005)Google Scholar
  2. 2.
    Pesic, M., van der Aalst, W.: A declarative approach for flexible business processes management. In: Eder, J., Dustdar, S. (eds.) BPM Workshops 2006. LNCS, vol. 4103, pp. 169–180. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  3. 3.
    Etzion, O., Niblett, P.: Event Processing in Action. Manning, Stammford (2010)Google Scholar
  4. 4.
    Ferreira, D.R., Gillblad, D.: Discovering process models from unlabelled event logs. In: Dayal, U., Eder, J., Koehler, J., Reijers, H.A. (eds.) BPM 2009. LNCS, vol. 5701, pp. 143–158. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  5. 5.
    Musaraj, K., Yoshida, T., Daniel, F., Hacid, M.S., Casati, F., Benatallah, B.: Message correlation and web service protocol mining from inaccurate logs. In: ICWS, pp. 259–266. IEEE Computer Society, Los Alamitos (2010)Google Scholar
  6. 6.
    Jacobsen, H.A., Muthusamy, V., Li, G.: The padres event processing network: Uniform querying of past and future events. It - Information Technology 51(5), 250–261 (2009)CrossRefGoogle Scholar
  7. 7.
    Gyllstrom, D., Wu, E., Chae, H.J., Diao, Y., Stahlberg, P., Anderson, G.: SASE Complex event processing over streams. In: Int. Conf. on Innovative Data Systems Research (2007)Google Scholar
  8. 8.
    Madden, S., Franklin, M.J.: Fjording the stream: An architecture for queries over streaming sensor data. In: International Conference on Data Engineering (2002)Google Scholar
  9. 9.
    EsperTech: Esper - Complex Event Processing (March 2011),
  10. 10.
    Brenna, L., Gehrke, J., Hong, M., Johansen, D.: Distributed event stream processing with non-deterministic finite automata. In: DEBS, pp. 1–12. ACM, New York (2009)CrossRefGoogle Scholar
  11. 11.
    Weidlich, M., Polyvyanyy, A., Mendling, J., Weske, M.: Efficient computation of causal behavioural profiles using structural decomposition. In: Lilius, J., Penczek, W. (eds.) PETRI NETS 2010. LNCS, vol. 6128, pp. 63–83. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  12. 12.
    Weidlich, M., Mendling, J., Weske, M.: Efficient consistency measurement based on behavioral profiles of process models. IEEE Trans. Software Eng. 37(3), 410–429 (2011)CrossRefGoogle Scholar
  13. 13.
    Bornhövd, C., Lin, T., Haller, S., Schaper, J.: Integrating automatic data acquisition with business processes experiences with sap’s auto-id infrastructure. In: Int. Conference on Very Large Data Bases, VLDB Endowment, pp. 1182–1188 (2004)Google Scholar
  14. 14.
    Weidlich, M., Polyvyanyy, A., Desai, N., Mendling, J., Weske, M.: Process compliance analysis based on behavioural profiles. Inf. Syst. 36(7), 1009–1025 (2011)CrossRefzbMATHGoogle Scholar
  15. 15.
    Hollingsworth, D.: The Workflow Reference Model. TC00-1003 Issue 1.1, Workflow Management Coalition (November 24, 1994)Google Scholar
  16. 16.
    Muehlen, M.: Workflow-based Process Controlling. In: Foundation, Design, and Implementation of Workflow-driven Process Information Systems, Logos, Berlin (2004)Google Scholar
  17. 17.
    van der Aalst, W., Reijers, H., Weijters, A., van Dongen, B., Alves de Medeiros, A., Song, M., Verbeek, H.: Business process mining: An industrial application. Information Systems 32(5), 713–732 (2007)CrossRefGoogle Scholar
  18. 18.
    Rozinat, A., van der Aalst, W.M.P.: Conformance checking of processes based on monitoring real behavior. Inf. Syst. 33(1), 64–95 (2008)CrossRefGoogle Scholar
  19. 19.
    van der Aalst, W.M.P., van Hee, K.M., van der Werf, J.M.E.M., Kumar, A., Verdonk, M.: Conceptual model for online auditing. Decision Support Systems 50(3), 636–647 (2011)CrossRefGoogle Scholar
  20. 20.
    Wetzstein, B., Karastoyanova, D., Kopp, O., Leymann, F., Zwink, D.: Cross-organizational process monitoring based on service choreographies. In: Shin, S.Y., Ossowski, S., Schumacher, M., Palakal, M.J., Hung, C.C. (eds.) Proceedings of ACM SAC, pp. 2485–2490. ACM, New York (2010)Google Scholar
  21. 21.
    Abadi, D.J., Ahmad, Y., Balazinska, M., Cetintemel, U., Cherniack, M., Hwang, J.H., Lindner, W., Maskey, A., Rasin, A., Ryvkina, E., Tatbul, N., Xing, Y., Zdonik, S.: The design of the Borealis stream processing engine. In: Int. Conf. on Innovative Data Systems Research, pp. 277–289 (2005)Google Scholar
  22. 22.
    Arasu, A., Babcock, B., Babu, S., Cieslewicz, J., Datar, M., Ito, K., Motwani, R., Srivastava, U., Widom, J.: Stream: The stanford data stream management system. Technical report, Department of Computer Science, Stanford University (2004)Google Scholar
  23. 23.
    Chandrasekaran, S., Cooper, O., Deshpande, A., Franklin, M.J., Hellerstein, J.M., Hong, W., Krishnamurthy, S., Madden, S., Raman, V., Reiss, F., Shah, M.A.: Telegraphcq: Continuous dataflow processing for an uncertain world. In: Int. Conf. on Innovative Data Systems Research (2003)Google Scholar
  24. 24.
    Madden, S.R., Franklin, M.J., Hellerstein, J.M., Hong, W.: TinyDB: An acquisitional query processing system for sensor networks. ACM Transactions on Database Systems (TODS) 30(1), 122–173 (2005)CrossRefGoogle Scholar
  25. 25.
    Yao, Y., Gehrke, J.: The cougar approach to in-network query processing in sensor networks. In: Proc. of the Intl. ACM Conf. on Management of Data, SIGMOD (2002)Google Scholar
  26. 26.
    Srivastava, U., Munagala, K., Widom, J.: Operator placement for in-network stream query processing. In: Proc. of PODS. ACM, New York (2005)Google Scholar
  27. 27.
    Schultz-Møller, N.P., Migliavacca, M., Pietzuch, P.: Distributed complex event processing with query rewriting. In: Proceedings of DEBS, pp. 1–12. ACM, New York (2009)CrossRefGoogle Scholar
  28. 28.
    Wu, E., Diao, Y., Rizvi, S.: High-performance complex event processing over streams. In: SIGMOD, pp. 407–418. ACM, New York (2006)Google Scholar
  29. 29.
    Weidlich, M., Ziekow, H., Mendling, J.: Optimising Complex Event Queries over Business Processes using Behavioural Profiles. In: Muehlen, M.z., Su, J. (eds.) J.1, H.4, D.2. Lecture Notes in Business Information Processing, vol. 66, pp. 743–754. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  30. 30.
    Garcia-Molina, H., Salem, K.: Sagas. ACM SIGMOD Record 16(3), 249–259 (1987)CrossRefGoogle Scholar
  31. 31.
    Georgakopoulos, D., Hornick, M.F., Sheth, A.P.: An overview of workflow management: From process modeling to workflow automation infrastructure. Distributed and Parallel Databases 3(2), 119–153 (1995)CrossRefGoogle Scholar
  32. 32.
    Alonso, G., Agrawal, D., Abbadi, A.E., Kamath, M., Günthör, R., Mohan, C.: Advanced transaction models in workflow contexts. In: Su, S.Y.W. (ed.) ICDE, pp. 574–581. IEEE Computer Society, Los Alamitos (1996)Google Scholar
  33. 33.
    Dayal, U., Hsu, M., Ladin, R.: Business Process Coordination: State of the Art, Trends, and Open Issues. In: Int. Conference on Very Large Databases, pp. 3–13. Morgan Kaufmann, San Francisco (2001)Google Scholar
  34. 34.
    Papazoglou, M.P.: Web services and business transactions. WWW 6(1), 49–91 (2003)CrossRefGoogle Scholar
  35. 35.
    Alonso, G., Casati, F., Kuno, H.A., Machiraju, V.: Web Services - Concepts, Architectures and Applications. In: Data-Centric Systems and Applications. Springer, Heidelberg (2004)Google Scholar
  36. 36.
    Cabrera, F., et al.: Web services atomic transaction (ws-atomictransaction). Technical report, IBM, Microsoft, BEA (2005)Google Scholar
  37. 37.
    Zhang, L.J.: Editorial: Context-aware application integration and transactional behaviors. IEEE T. Services Computing 3(1), 1 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Matthias Weidlich
    • 1
  • Holger Ziekow
    • 2
  • Jan Mendling
    • 3
  • Oliver Günther
    • 3
  • Mathias Weske
    • 1
  • Nirmit Desai
    • 4
  1. 1.Hasso-Plattner-InstituteUniversity of PotsdamGermany
  2. 2.AGT GermanyGermany
  3. 3.Humboldt-Universität zu BerlinGermany
  4. 4.IBM India Research LabsIndia

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