Facilitating the Quantitative Analysis ofComplexEvents through a Computational Intelligence Model-Driven Tool

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URI: http://hdl.handle.net/10498/21721
DOI: 10.1155/2019/2604148
ISSN: 1058-9244
ISSN: 1875-919X
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2019-07Department
Ingeniería InformáticaSource
Scientific Programming Volume 2019, Article ID 2604148Abstract
Complex event processing (CEP) is a computational intelligence technology capable of analyzing big data streams for event
pattern recognition in real time. In particular, this technology is vastly useful for analyzing multicriteria conditions in a pattern,
which will trigger alerts (complex events) upon their fulfillment. However, one of the main challenges to be faced by CEP is how to
define the quantitative analysis to be performed in response to the produced complex events. In this paper, we propose the use of
the MEdit4CEP-CPN model-driven tool as a solution for conducting such quantitative analysis of events of interest for an
application domain, without requiring knowledge of any scientific programming language for implementing the pattern
conditions. Precisely, MEdit4CEP-CPN facilitates domain experts to graphically model event patterns, transform them into a
Prioritized Colored Petri Net (PCPN) model, modify its initial marking depending on the application scenario, and make the
quantitative analysis through the simulation and monitor capabilities provided by CPN tools.
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