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

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...

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Autores principales: Foguelman, Daniel J., Bonaventura, Matías, Castro, Rodrigo
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2017
Materias:
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/63170
http://www.clei2017-46jaiio.sadio.org.ar/sites/default/files/Mem/AGRANDA/AGRANDA-03.pdf
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id I19-R120-10915-63170
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Simulation
Análisis de Datos
Automatización
spellingShingle Ciencias Informáticas
Simulation
Análisis de Datos
Automatización
Foguelman, Daniel J.
Bonaventura, Matías
Castro, Rodrigo
Systematic data analysis-based validation of simulation models with heterogeneous data sources
topic_facet Ciencias Informáticas
Simulation
Análisis de Datos
Automatización
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.
format Objeto de conferencia
Objeto de conferencia
author Foguelman, Daniel J.
Bonaventura, Matías
Castro, Rodrigo
author_facet Foguelman, Daniel J.
Bonaventura, Matías
Castro, Rodrigo
author_sort Foguelman, Daniel J.
title Systematic data analysis-based validation of simulation models with heterogeneous data sources
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
publishDate 2017
url http://sedici.unlp.edu.ar/handle/10915/63170
http://www.clei2017-46jaiio.sadio.org.ar/sites/default/files/Mem/AGRANDA/AGRANDA-03.pdf
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AT castrorodrigo systematicdataanalysisbasedvalidationofsimulationmodelswithheterogeneousdatasources
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