ModeL4CEP: Graphical domain-specific modeling languages for CEP domains and event patterns

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URI: http://hdl.handle.net/10498/20954
DOI: 10.1016/j.eswa.2015.06.045
ISSN: 0957-4174
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2015-11Department
Ingeniería InformáticaSource
Boubeta-Puig, J., Ortiz, G., & Medina-Bulo, I. (2015). ModeL4CEP: Graphical domain-specific modeling languages for CEP domains and event patterns. Expert Systems with Applications, 42(21), 8095–8110. https://doi.org/10.1016/j.eswa.2015.06.045Abstract
Complex event processing (CEP) is a cutting-edge technology that allows the analysis and correlation of large volumes of data with the aim of detecting complex and meaningful events through the use of event patterns, as well as permitting the inference of valuable knowledge for end users. Despite the great advantages that CEP can bring to expert or intelligent business systems, it poses a substantial challenge to their users, who are business experts but do not have the necessary knowledge and experience using this technology. The main problem these users have to face is precisely hand-writing the code for event pattern definition, which requires them to implement the conditions to be met to detect relevant situations for the domain in question by using a particular event processing language (EPL). In order to respond to this need, in this paper we propose both a graphical domain-specific modeling language (DSML) for facilitating CEP domain definitions by domain experts, and a graphical DSML for event pattern definition by non-technological users. The proposed languages provide high expressiveness and flexibility and are independent of event patterns and actions’ implementation code. This way, domain experts can define the relevant event types and patterns within their business domain, without having to be experts on EPL programming, nor on other complicated computer science technological issues, beyond an understandable and intuitive graphical definition. Furthermore, with these DSMLs, users will also be able to define the actions to be automatically taken once a pattern is detected in the system. Further benefits of these DSMLs are evaluated and discussed in depth in this paper.
Subjects
Complex event processing; Model-driven development; Domain-specific modeling language; Event processing languageCollections
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