Assessing SLA compliance from Palladio component models

Service providers face the challenge of meeting service-level agreements (SLAs) under uncertainty on the application actual performance. The performance heavily depends on the characteristics of the hardware on which the application is deployed, on the application architecture, as well as on the use...

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Autores:
Tipo de recurso:
Fecha de publicación:
2014
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/28496
Acceso en línea:
https://doi.org/10.1109/SYNASC.2013.60
https://repository.urosario.edu.co/handle/10336/28496
Palabra clave:
Computational modeling
Analytical models
Phase change materials
Program processors
Servers
Delays
Throughput
Rights
License
Restringido (Acceso a grupos específicos)
id EDOCUR2_30da0e0061aab045320227ba1b58e4d4
oai_identifier_str oai:repository.urosario.edu.co:10336/28496
network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
spelling 80035202600693f31c7-5e59-4d88-b96a-2175836ec1b02020-08-28T15:49:14Z2020-08-28T15:49:14Z2014-05-26Service providers face the challenge of meeting service-level agreements (SLAs) under uncertainty on the application actual performance. The performance heavily depends on the characteristics of the hardware on which the application is deployed, on the application architecture, as well as on the user workload. Although many models have been proposed for the performance prediction of software applications, most of them focus on average measures, e.g., mean response times. However, SLAs are often set in terms of percentiles, such that a given portion of requests receive a predefined service level, e.g., 95% of the requests should face a response time of at most 10 ms. To enable the effective prediction of this type of measures, in this paper we use fluid models for the computation of the probability distribution of performance measures relevant for SLAs. Our models are automatically built from a Palladio Component Model (PCM) instance, thus allowing the SLA assessment directly from the PCM specification. This provides an scalable alternative for SLA assessment within the PCM framework, as currently this is supported by means of simulation only.application/pdfhttps://doi.org/10.1109/SYNASC.2013.60ISBN: 978-1-4799-3035-7EISBN: 978-1-4799-3036-4https://repository.urosario.edu.co/handle/10336/28496engIEEE4164092013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, ISBN: 978-1-4799-3035-7;EISBN: 978-1-4799-3036-4 (2013); pp. 409-416https://ieeexplore.ieee.org/document/6821177?section=abstractRestringido (Acceso a grupos específicos)http://purl.org/coar/access_right/c_16ec2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computinginstname:Universidad del Rosarioreponame:Repositorio Institucional EdocURComputational modelingAnalytical modelsPhase change materialsProgram processorsServersDelaysThroughputAssessing SLA compliance from Palladio component modelsEvaluación del cumplimiento de SLA a partir de modelos de componentes de PalladiobookPartParte de librohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_3248Pérez, Juan F.Casale, Giuliano10336/28496oai:repository.urosario.edu.co:10336/284962021-09-23 12:33:13.786https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co
dc.title.spa.fl_str_mv Assessing SLA compliance from Palladio component models
dc.title.TranslatedTitle.spa.fl_str_mv Evaluación del cumplimiento de SLA a partir de modelos de componentes de Palladio
title Assessing SLA compliance from Palladio component models
spellingShingle Assessing SLA compliance from Palladio component models
Computational modeling
Analytical models
Phase change materials
Program processors
Servers
Delays
Throughput
title_short Assessing SLA compliance from Palladio component models
title_full Assessing SLA compliance from Palladio component models
title_fullStr Assessing SLA compliance from Palladio component models
title_full_unstemmed Assessing SLA compliance from Palladio component models
title_sort Assessing SLA compliance from Palladio component models
dc.subject.keyword.spa.fl_str_mv Computational modeling
Analytical models
Phase change materials
Program processors
Servers
Delays
Throughput
topic Computational modeling
Analytical models
Phase change materials
Program processors
Servers
Delays
Throughput
description Service providers face the challenge of meeting service-level agreements (SLAs) under uncertainty on the application actual performance. The performance heavily depends on the characteristics of the hardware on which the application is deployed, on the application architecture, as well as on the user workload. Although many models have been proposed for the performance prediction of software applications, most of them focus on average measures, e.g., mean response times. However, SLAs are often set in terms of percentiles, such that a given portion of requests receive a predefined service level, e.g., 95% of the requests should face a response time of at most 10 ms. To enable the effective prediction of this type of measures, in this paper we use fluid models for the computation of the probability distribution of performance measures relevant for SLAs. Our models are automatically built from a Palladio Component Model (PCM) instance, thus allowing the SLA assessment directly from the PCM specification. This provides an scalable alternative for SLA assessment within the PCM framework, as currently this is supported by means of simulation only.
publishDate 2014
dc.date.created.spa.fl_str_mv 2014-05-26
dc.date.accessioned.none.fl_str_mv 2020-08-28T15:49:14Z
dc.date.available.none.fl_str_mv 2020-08-28T15:49:14Z
dc.type.eng.fl_str_mv bookPart
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_3248
dc.type.spa.spa.fl_str_mv Parte de libro
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1109/SYNASC.2013.60
dc.identifier.issn.none.fl_str_mv ISBN: 978-1-4799-3035-7
EISBN: 978-1-4799-3036-4
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/28496
url https://doi.org/10.1109/SYNASC.2013.60
https://repository.urosario.edu.co/handle/10336/28496
identifier_str_mv ISBN: 978-1-4799-3035-7
EISBN: 978-1-4799-3036-4
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.citationEndPage.none.fl_str_mv 416
dc.relation.citationStartPage.none.fl_str_mv 409
dc.relation.citationTitle.none.fl_str_mv 2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing
dc.relation.ispartof.spa.fl_str_mv 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, ISBN: 978-1-4799-3035-7;EISBN: 978-1-4799-3036-4 (2013); pp. 409-416
dc.relation.uri.spa.fl_str_mv https://ieeexplore.ieee.org/document/6821177?section=abstract
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_16ec
dc.rights.acceso.spa.fl_str_mv Restringido (Acceso a grupos específicos)
rights_invalid_str_mv Restringido (Acceso a grupos específicos)
http://purl.org/coar/access_right/c_16ec
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv IEEE
dc.source.spa.fl_str_mv 2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing
institution Universidad del Rosario
dc.source.instname.none.fl_str_mv instname:Universidad del Rosario
dc.source.reponame.none.fl_str_mv reponame:Repositorio Institucional EdocUR
repository.name.fl_str_mv Repositorio institucional EdocUR
repository.mail.fl_str_mv edocur@urosario.edu.co
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