Semantic Event Correlation Using Ontologies
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Abstract
Complex event processing (CEP) is a software architecture paradigm that aims at low latency, high throughput, and quick adaptability of applications for supporting and improving event-driven business processes. Events sensed in real time are the basic information units on which CEP applications operate and react in self-contained decision cycles based on defined processing logic and rules. Event correlation is necessary to relate events gathered from various sources for detecting patterns and situations of interest in the business context. Unfortunately, event correlation has been limited to syntactically identical attribute values instead of addressing semantically equivalent attribute meanings. Semantic equivalence is particularly relevant if events come from organizations that use different terminologies for common concepts.
In this paper, we introduce an approach that uses semantic technologies, in our case ontologies, for the definition of event correlations to facilitate semantic event correlation derived from semantic equivalence, inherited meaning, and relationships between different terms or entities. We evaluate the practical application of three types of semantic correlation based on use cases that are relevant to the real-world domain of industrial production automation. Major results of the evaluation show that semantic correlation enables functions for CEP that traditional syntactic correlation does not allow at all.
Keywords
Complex event processing semantic event correlation ontologyPreview
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References
- 1.Abadi, D., Ahmad, Y., Balazinska, M., Çetintemel, U., Cherniack, M., Hwang, J., Lindner, W., Maskey, A., Rasin, A., Ryvkina, E., Tatbul, N., Xing, Y., Zdonik, S.: The Design of the Borealis Stream Processing Engine. In: Proc. of the Conf. on Innovative Data Systems Research, pp. 277–289 (2005)Google Scholar
- 2.Baclawski, K., Kokar, M., Kogut, P., Hart, L., Smith, J., Holmes, W., Letkowski, J., Aronson, M.: Extending UML to Support Ontology Engineering for the Semantic Web. In: Fourth International Conference on UML (2001)Google Scholar
- 3.Calero, C., Ruiz, F., Piattini, M.: Ontologies for Software Engineering and Technology. Springer, Berlin (2007)Google Scholar
- 4.Chandrasekaran, B., Josephson, J.R., Richard Benjamins, V.: What Are Ontologies, and Why Do We Need Them? IEEE Intelligent Systems (1999)Google Scholar
- 5.Esper (March 20, 2008), http://esper.codehaus.org/
- 6.Hackathorn, R.: Current practices in active data warehousing. DMReview (2002)Google Scholar
- 7.Happel, H., Seedorf, S.: Applications of Ontologies in Software Engineering. In: Proc. of the Workshop on Semantic Web Enabled Software Engineering, SWESE (2006)Google Scholar
- 8.Luckham, D.: The Power Of Events. Addison Wesley, Reading (2005)Google Scholar
- 9.Rozsnyai, S., Vecera, R., Schiefer, J., Schatten, A.: Event Cloud - Searching for Correlated Business Events. In: CEC/EEE, pp. 409–420. IEEE Computer Society, Los Alamitos (2007)Google Scholar
- 10.Schiefer, J., McGregor, C.: Correlating events for monitoring business processes. In: ICEIS, vol. 1, pp. 320–327 (2004)Google Scholar
- 11.Schiefer, J., Rozsnyai, S., Rauscher, C., Saurer, G.: Event-driven rules for sensing and responding to business situations. In: Proc. DEBS, pp. 198–205. ACM, New York (2007)CrossRefGoogle Scholar
- 12.Schiefer, J., Seufert, A.: Management and controlling of time-sensitive business processes with sense & respond. In: CIMCA/IAWTIC, pp. 77–82. IEEE, Los Alamitos (2005)Google Scholar
- 13.Vecera, R., Rozsnyai, S., Roth, H.: Indexing and search of correlated business events. Ares 0, 1124–1134 (2007)Google Scholar