Abstract
Complex Event Processing handles processing of a large number of heterogeneous events and pattern detection over multiple event streams in real-time. Situations of interests are modeled using event patterns which describe a specific situation in an event processing language. In order to leverage the usage of event processing in everyday situations, a clear methodology for the identification and definition of events and event patterns is needed. In this paper, we propose an end-to-end methodology for designing event processing systems. This methodology integrates domain knowledge modeled during the setup phase of event processing with a high-level event pattern language which allows users to create specific business-related patterns. In addition, our methodology regards the circumstance that some patterns might have to be defined by technical experts and therefore introduces an actor model. Our approach is validated based on a real use case of a supplier of convenience stores.
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References
Bughin, J., Chui, M., Manyika, J.: Clouds, big data and smart assets: Ten tech-enabled business trends to watch. In: McKinseyQuarterly (2010)
Zikopoulos, P., Eaton, C.: Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data. McGraw-Hill Osborne Media (2011)
Luckham, D.: The power of events: An Introduction to Complex Event Processing in Distributed Enterprise Systems. Addison-Wesley, Reading (2002)
Anicic, D., Rudolph, S., Fodor, P., Stojanovic, N.: Real-Time Complex Event Recognition and Reasoning – A Logic Programming Approach, Applied Artificial Intelligence, vol. 26 (2012), Special Issue on Event Recognition
Wasserkrug, S., Gal, A., Etzion, O., Turchin, Y.: Complex event processing over uncertain data. In: Proceedings of the Second International Conference on Distributed Event-Based Systems (DEBS 2008), pp. 253–264. ACM, New York (2008)
Sen, S., Stojanovic, N.: GRUVe: A Methodology for Complex Event Pattern Life Cycle Management. In: Pernici, B. (ed.) CAiSE 2010. LNCS, vol. 6051, pp. 209–223. Springer, Heidelberg (2010)
Obweger, H., Schiefer, J., Suntinger, M., Breier, F., Thullner, R.: Complex Event Processing off the Shelf – Rapid Development of Event-Driven Applications with Solution Templates. In: Proceedings of the 19th Mediterranean Conference on Control and Automation, Corfu, Greece (2011)
Vidačković, K., Kellner, I., Donald, J.: Business-oriented development methodology for complex event processing: demonstration of an integrated approach for process monitoring. In: Proceedings of the Fourth ACM International Conference on Distributed Event-Based Systems (DEBS 2010), pp. 111–112. ACM, New York (2010)
Sharon, G., Etzion, O.: Event-processing network model and implementation. IBM Systems Journal 47(2), 321–334 (2008)
Etzion, O., Niblett, P.: Event Processing in Action. Manning (2011)
Obweger, H., Schiefer, J., Suntinger, M., Kepplinger, P., Rozsnyai, S.: User-oriented rule management for event-based applications. In: Proceedings of the 5th ACM International Conference on Distributed Event-Based System (DEBS 2011), pp. 39–48. ACM, New York (2011)
Veres, C, Sampson, J, Cox, K., Bleistein, S., Verner, J.: An ontology based approach for supporting business IT alignment In: Complex Intelligent Systems and Their Applications. Springer Optimization and Its Applications (41). Springer, pp. 21-42.
Bleistein, S.: B-SCP an integrated approach for validating alignment of organizational IT requirements with competitive business strategy. PhD Thesis (2006)
Sowa, J.F., Zachman, J.: A Extending and formalizing the framework for information systems architecture. IBM Systems Journal 31(3), 590–616 (1992)
Riemer, D., Stojanovic, L., Stojanovic, N.: Using Complex Event Processing for Modeling Semantic Requests in Real-Time Social Media Monitoring. In: Sixth International AAAI Conference on Weblogs and Social Media (May 2012)
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Riemer, D., Stojanovic, N., Stojanovic, L. (2013). A Methodology for Designing Events and Patterns in Fast Data Processing. In: Salinesi, C., Norrie, M.C., Pastor, Ó. (eds) Advanced Information Systems Engineering. CAiSE 2013. Lecture Notes in Computer Science, vol 7908. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38709-8_9
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DOI: https://doi.org/10.1007/978-3-642-38709-8_9
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