Facilitating the Quantitative Analysis of Complex Events through a Computational Intelligence Model-Driven Tool

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)...

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Published inScientific programming Vol. 2019; no. 2019; pp. 1 - 17
Main Authors Boubeta-Puig, Juan, Valero, Valentín, Macià, Hermenegilda, Díaz, Gregorio, Ortiz, Guadalupe
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Publishing Corporation 2019
Hindawi
John Wiley & Sons, Inc
Subjects
Artificial intelligence
Big Data
Computer simulation
Data transmission
Engineering
Intelligence
International conferences
Multiple criterion
Pattern recognition
Petri nets
Programming languages
Quantitative analysis
Semantics
Software
Subject specialists
Technology assessment
Online AccessGet full text
ISSN1058-9244
1875-919X
1875-919X
DOI10.1155/2019/2604148

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Abstract 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.
AbstractList 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.
Author Valero, Valentín
Ortiz, Guadalupe
Boubeta-Puig, Juan
Macià, Hermenegilda
Díaz, Gregorio
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Copyright Copyright © 2019 Gregorio Díaz et al.
Copyright © 2019 Gregorio Díaz et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. http://creativecommons.org/licenses/by/4.0
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SubjectTerms Artificial intelligence
Big Data
Computer simulation
Data transmission
Engineering
Intelligence
International conferences
Multiple criterion
Pattern recognition
Petri nets
Programming languages
Quantitative analysis
Semantics
Software
Subject specialists
Technology assessment
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Title Facilitating the Quantitative Analysis of Complex Events through a Computational Intelligence Model-Driven Tool
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