Systematic data analysis-based validation of simulation models with heterogeneous data sources

Autores
Foguelman, Daniel J.; Bonaventura, Matías; Castro, Rodrigo
Año de publicación
2017
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Complex networked computer systems are subjected to upgrades on a continuous basis. Modeling and simulation (M&S) of such systems helps with guiding their engineering processes when testing design options on the real system is not an option. Too often many system’s operational conditions need to be assumed in order to focus on the questions at hand, a typical case being the exogenous workload. Meanwhile, soaring amounts of monitoring information is logged to analyze the system’s performance in search for improvement opportunities. Concurrently, research questions mutate as operational conditions vary throughout its lifetime. This context poses many challenges to assess the validity of simulation models. As the empirical knowledge base of the system grows, the question arises whether a simulation model that was once deemed valid could be invalidated in the context of unprecedented operation conditions. This work presents a conceptual framework and a practical prototype that helps with answering this question in a systematic, automated way. MASADA parses recorded operation intervals and automatically parameterizes, launches, and validates simulation experiments. MASADA has been tested in the data acquisition network of the ATLAS particle physics experiment at CERN. The result is an efficient framework for validating our models on a continuous basis as new particle collisions impose unpredictable network workloads.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
Materia
Ciencias Informáticas
Simulation
Análisis de Datos
Automatización
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-sa/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/63170

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spelling Systematic data analysis-based validation of simulation models with heterogeneous data sourcesFoguelman, Daniel J.Bonaventura, MatíasCastro, RodrigoCiencias InformáticasSimulationAnálisis de DatosAutomatizaciónComplex networked computer systems are subjected to upgrades on a continuous basis. Modeling and simulation (M&S) of such systems helps with guiding their engineering processes when testing design options on the real system is not an option. Too often many system’s operational conditions need to be assumed in order to focus on the questions at hand, a typical case being the exogenous workload. Meanwhile, soaring amounts of monitoring information is logged to analyze the system’s performance in search for improvement opportunities. Concurrently, research questions mutate as operational conditions vary throughout its lifetime. This context poses many challenges to assess the validity of simulation models. As the empirical knowledge base of the system grows, the question arises whether a simulation model that was once deemed valid could be invalidated in the context of unprecedented operation conditions. This work presents a conceptual framework and a practical prototype that helps with answering this question in a systematic, automated way. MASADA parses recorded operation intervals and automatically parameterizes, launches, and validates simulation experiments. MASADA has been tested in the data acquisition network of the ATLAS particle physics experiment at CERN. The result is an efficient framework for validating our models on a continuous basis as new particle collisions impose unpredictable network workloads.Sociedad Argentina de Informática e Investigación Operativa (SADIO)2017-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf10-12http://sedici.unlp.edu.ar/handle/10915/63170enginfo:eu-repo/semantics/altIdentifier/url/http://www.clei2017-46jaiio.sadio.org.ar/sites/default/files/Mem/AGRANDA/AGRANDA-03.pdfinfo:eu-repo/semantics/altIdentifier/issn/2451-7569info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-sa/3.0/Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:08:19Zoai:sedici.unlp.edu.ar:10915/63170Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:08:19.981SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Systematic data analysis-based validation of simulation models with heterogeneous data sources
title Systematic data analysis-based validation of simulation models with heterogeneous data sources
spellingShingle Systematic data analysis-based validation of simulation models with heterogeneous data sources
Foguelman, Daniel J.
Ciencias Informáticas
Simulation
Análisis de Datos
Automatización
title_short Systematic data analysis-based validation of simulation models with heterogeneous data sources
title_full Systematic data analysis-based validation of simulation models with heterogeneous data sources
title_fullStr Systematic data analysis-based validation of simulation models with heterogeneous data sources
title_full_unstemmed Systematic data analysis-based validation of simulation models with heterogeneous data sources
title_sort Systematic data analysis-based validation of simulation models with heterogeneous data sources
dc.creator.none.fl_str_mv Foguelman, Daniel J.
Bonaventura, Matías
Castro, Rodrigo
author Foguelman, Daniel J.
author_facet Foguelman, Daniel J.
Bonaventura, Matías
Castro, Rodrigo
author_role author
author2 Bonaventura, Matías
Castro, Rodrigo
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Simulation
Análisis de Datos
Automatización
topic Ciencias Informáticas
Simulation
Análisis de Datos
Automatización
dc.description.none.fl_txt_mv Complex networked computer systems are subjected to upgrades on a continuous basis. Modeling and simulation (M&S) of such systems helps with guiding their engineering processes when testing design options on the real system is not an option. Too often many system’s operational conditions need to be assumed in order to focus on the questions at hand, a typical case being the exogenous workload. Meanwhile, soaring amounts of monitoring information is logged to analyze the system’s performance in search for improvement opportunities. Concurrently, research questions mutate as operational conditions vary throughout its lifetime. This context poses many challenges to assess the validity of simulation models. As the empirical knowledge base of the system grows, the question arises whether a simulation model that was once deemed valid could be invalidated in the context of unprecedented operation conditions. This work presents a conceptual framework and a practical prototype that helps with answering this question in a systematic, automated way. MASADA parses recorded operation intervals and automatically parameterizes, launches, and validates simulation experiments. MASADA has been tested in the data acquisition network of the ATLAS particle physics experiment at CERN. The result is an efficient framework for validating our models on a continuous basis as new particle collisions impose unpredictable network workloads.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
description Complex networked computer systems are subjected to upgrades on a continuous basis. Modeling and simulation (M&S) of such systems helps with guiding their engineering processes when testing design options on the real system is not an option. Too often many system’s operational conditions need to be assumed in order to focus on the questions at hand, a typical case being the exogenous workload. Meanwhile, soaring amounts of monitoring information is logged to analyze the system’s performance in search for improvement opportunities. Concurrently, research questions mutate as operational conditions vary throughout its lifetime. This context poses many challenges to assess the validity of simulation models. As the empirical knowledge base of the system grows, the question arises whether a simulation model that was once deemed valid could be invalidated in the context of unprecedented operation conditions. This work presents a conceptual framework and a practical prototype that helps with answering this question in a systematic, automated way. MASADA parses recorded operation intervals and automatically parameterizes, launches, and validates simulation experiments. MASADA has been tested in the data acquisition network of the ATLAS particle physics experiment at CERN. The result is an efficient framework for validating our models on a continuous basis as new particle collisions impose unpredictable network workloads.
publishDate 2017
dc.date.none.fl_str_mv 2017-09
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info:eu-repo/semantics/altIdentifier/issn/2451-7569
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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