Towards Lightweight Dynamic Adaptation : A Framework and its Evaluation

Autores
Rocha, Leonardo M.; Sen, Sagar; Moisan, Sabine; Rigault, Jean-Paul
Año de publicación
2011
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Many modern systems must run in continually changing contexts. For example, a computer vision system to detect vandalism in train stations must function during the day and at night. The software components for image acquisition and people detection used during daytime may not be the same as those used at night. The system must adapt by replacing running components such as image acquisition from color to infra-red. This adaptation involves context detection, decision on change in components, followed by seamless execution of a new configuration of components. All this must occur at runtime while minimizing the impact of dynamic change on continuity and loss in performance. We present Girgit, a lightweight Python-based framework for building dynamic adaptive software systems. We evaluate it by building a dynamically adaptive vision system followed by performing rigorous experiments to determine its continuity and performance.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Adaptive Systems
Dynamic Adaptive Systems
Software Architecture
Framework
Vision System
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/125493
Acceder
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network_name_str SEDICI (UNLP)
spelling Towards Lightweight Dynamic Adaptation : A Framework and its EvaluationRocha, Leonardo M.Sen, SagarMoisan, SabineRigault, Jean-PaulCiencias InformáticasAdaptive SystemsDynamic Adaptive SystemsSoftware ArchitectureFrameworkVision SystemMany modern systems must run in continually changing contexts. For example, a computer vision system to detect vandalism in train stations must function during the day and at night. The software components for image acquisition and people detection used during daytime may not be the same as those used at night. The system must adapt by replacing running components such as image acquisition from color to infra-red. This adaptation involves context detection, decision on change in components, followed by seamless execution of a new configuration of components. All this must occur at runtime while minimizing the impact of dynamic change on continuity and loss in performance. We present Girgit, a lightweight Python-based framework for building dynamic adaptive software systems. We evaluate it by building a dynamically adaptive vision system followed by performing rigorous experiments to determine its continuity and performance.Sociedad Argentina de Informática e Investigación Operativa2011-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf156-167http://sedici.unlp.edu.ar/handle/10915/125493enginfo:eu-repo/semantics/altIdentifier/url/https://40jaiio.sadio.org.ar/sites/default/files/T2011/ASSE/783.pdfinfo:eu-repo/semantics/altIdentifier/issn/1850-2792info:eu-repo/semantics/reference/hdl/10915/135250info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:22:02Zoai:sedici.unlp.edu.ar:10915/125493Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:22:02.314SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Towards Lightweight Dynamic Adaptation : A Framework and its Evaluation
title Towards Lightweight Dynamic Adaptation : A Framework and its Evaluation
spellingShingle Towards Lightweight Dynamic Adaptation : A Framework and its Evaluation
Rocha, Leonardo M.
Ciencias Informáticas
Adaptive Systems
Dynamic Adaptive Systems
Software Architecture
Framework
Vision System
title_short Towards Lightweight Dynamic Adaptation : A Framework and its Evaluation
title_full Towards Lightweight Dynamic Adaptation : A Framework and its Evaluation
title_fullStr Towards Lightweight Dynamic Adaptation : A Framework and its Evaluation
title_full_unstemmed Towards Lightweight Dynamic Adaptation : A Framework and its Evaluation
title_sort Towards Lightweight Dynamic Adaptation : A Framework and its Evaluation
dc.creator.none.fl_str_mv Rocha, Leonardo M.
Sen, Sagar
Moisan, Sabine
Rigault, Jean-Paul
author Rocha, Leonardo M.
author_facet Rocha, Leonardo M.
Sen, Sagar
Moisan, Sabine
Rigault, Jean-Paul
author_role author
author2 Sen, Sagar
Moisan, Sabine
Rigault, Jean-Paul
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Adaptive Systems
Dynamic Adaptive Systems
Software Architecture
Framework
Vision System
topic Ciencias Informáticas
Adaptive Systems
Dynamic Adaptive Systems
Software Architecture
Framework
Vision System
dc.description.none.fl_txt_mv Many modern systems must run in continually changing contexts. For example, a computer vision system to detect vandalism in train stations must function during the day and at night. The software components for image acquisition and people detection used during daytime may not be the same as those used at night. The system must adapt by replacing running components such as image acquisition from color to infra-red. This adaptation involves context detection, decision on change in components, followed by seamless execution of a new configuration of components. All this must occur at runtime while minimizing the impact of dynamic change on continuity and loss in performance. We present Girgit, a lightweight Python-based framework for building dynamic adaptive software systems. We evaluate it by building a dynamically adaptive vision system followed by performing rigorous experiments to determine its continuity and performance.
Sociedad Argentina de Informática e Investigación Operativa
description Many modern systems must run in continually changing contexts. For example, a computer vision system to detect vandalism in train stations must function during the day and at night. The software components for image acquisition and people detection used during daytime may not be the same as those used at night. The system must adapt by replacing running components such as image acquisition from color to infra-red. This adaptation involves context detection, decision on change in components, followed by seamless execution of a new configuration of components. All this must occur at runtime while minimizing the impact of dynamic change on continuity and loss in performance. We present Girgit, a lightweight Python-based framework for building dynamic adaptive software systems. We evaluate it by building a dynamically adaptive vision system followed by performing rigorous experiments to determine its continuity and performance.
publishDate 2011
dc.date.none.fl_str_mv 2011-09
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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info:ar-repo/semantics/documentoDeConferencia
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status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/125493
url http://sedici.unlp.edu.ar/handle/10915/125493
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://40jaiio.sadio.org.ar/sites/default/files/T2011/ASSE/783.pdf
info:eu-repo/semantics/altIdentifier/issn/1850-2792
info:eu-repo/semantics/reference/hdl/10915/135250
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
156-167
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reponame_str SEDICI (UNLP)
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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