Towards a predictive load balancing method based on multiples resources

Autores
Gallard, Raúl Hector; Piccoli, María Fabiana; García, José Luis
Año de publicación
2000
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Processors load unbalance in distributed systems is one of the main problems, because ít involves system performance degradation. Load balance algorithms try to improve the system global performance through migration of processes, but they present also an additional problem, known as instability: lt happens when processes spend an excessive amount of time migrating among different system nodes. In arder to diminish this cost without affecting the mean system response time, load balancíng algoríthms based on dífferent strategíes have been proposed. Multiple Resources Predictíve Load Balance Strategy (MRPLBS), ís a new predíctive, dynamic and nonpreemptive strategy for balancing multiple resources. The predictive approach is based on estimations computed as weighed exponential averages of the load of each node in the system. This paper presents MRPLBS' system architecture and its performance and system a comparison on different scenarios against Random Load Balancing. The number of requirements, the mean response time, the number of failed migratíons and the percentage of acceptance are shown
I Workshop de Procesamiento Distribuido y Paralelo (WPDP)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Distributed Systems
load balancing strategies
multiple resources metric
mean response time
migrations
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/23359
Acceder
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repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Towards a predictive load balancing method based on multiples resourcesGallard, Raúl HectorPiccoli, María FabianaGarcía, José LuisCiencias InformáticasDistributed Systemsload balancing strategiesmultiple resources metricmean response timemigrationsProcessors load unbalance in distributed systems is one of the main problems, because ít involves system performance degradation. Load balance algorithms try to improve the system global performance through migration of processes, but they present also an additional problem, known as instability: lt happens when processes spend an excessive amount of time migrating among different system nodes. In arder to diminish this cost without affecting the mean system response time, load balancíng algoríthms based on dífferent strategíes have been proposed. Multiple Resources Predictíve Load Balance Strategy (MRPLBS), ís a new predíctive, dynamic and nonpreemptive strategy for balancing multiple resources. The predictive approach is based on estimations computed as weighed exponential averages of the load of each node in the system. This paper presents MRPLBS' system architecture and its performance and system a comparison on different scenarios against Random Load Balancing. The number of requirements, the mean response time, the number of failed migratíons and the percentage of acceptance are shownI Workshop de Procesamiento Distribuido y Paralelo (WPDP)Red de Universidades con Carreras en Informática (RedUNCI)2000-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/23359enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:28:12Zoai:sedici.unlp.edu.ar:10915/23359Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:28:13.032SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Towards a predictive load balancing method based on multiples resources
title Towards a predictive load balancing method based on multiples resources
spellingShingle Towards a predictive load balancing method based on multiples resources
Gallard, Raúl Hector
Ciencias Informáticas
Distributed Systems
load balancing strategies
multiple resources metric
mean response time
migrations
title_short Towards a predictive load balancing method based on multiples resources
title_full Towards a predictive load balancing method based on multiples resources
title_fullStr Towards a predictive load balancing method based on multiples resources
title_full_unstemmed Towards a predictive load balancing method based on multiples resources
title_sort Towards a predictive load balancing method based on multiples resources
dc.creator.none.fl_str_mv Gallard, Raúl Hector
Piccoli, María Fabiana
García, José Luis
author Gallard, Raúl Hector
author_facet Gallard, Raúl Hector
Piccoli, María Fabiana
García, José Luis
author_role author
author2 Piccoli, María Fabiana
García, José Luis
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Distributed Systems
load balancing strategies
multiple resources metric
mean response time
migrations
topic Ciencias Informáticas
Distributed Systems
load balancing strategies
multiple resources metric
mean response time
migrations
dc.description.none.fl_txt_mv Processors load unbalance in distributed systems is one of the main problems, because ít involves system performance degradation. Load balance algorithms try to improve the system global performance through migration of processes, but they present also an additional problem, known as instability: lt happens when processes spend an excessive amount of time migrating among different system nodes. In arder to diminish this cost without affecting the mean system response time, load balancíng algoríthms based on dífferent strategíes have been proposed. Multiple Resources Predictíve Load Balance Strategy (MRPLBS), ís a new predíctive, dynamic and nonpreemptive strategy for balancing multiple resources. The predictive approach is based on estimations computed as weighed exponential averages of the load of each node in the system. This paper presents MRPLBS' system architecture and its performance and system a comparison on different scenarios against Random Load Balancing. The number of requirements, the mean response time, the number of failed migratíons and the percentage of acceptance are shown
I Workshop de Procesamiento Distribuido y Paralelo (WPDP)
Red de Universidades con Carreras en Informática (RedUNCI)
description Processors load unbalance in distributed systems is one of the main problems, because ít involves system performance degradation. Load balance algorithms try to improve the system global performance through migration of processes, but they present also an additional problem, known as instability: lt happens when processes spend an excessive amount of time migrating among different system nodes. In arder to diminish this cost without affecting the mean system response time, load balancíng algoríthms based on dífferent strategíes have been proposed. Multiple Resources Predictíve Load Balance Strategy (MRPLBS), ís a new predíctive, dynamic and nonpreemptive strategy for balancing multiple resources. The predictive approach is based on estimations computed as weighed exponential averages of the load of each node in the system. This paper presents MRPLBS' system architecture and its performance and system a comparison on different scenarios against Random Load Balancing. The number of requirements, the mean response time, the number of failed migratíons and the percentage of acceptance are shown
publishDate 2000
dc.date.none.fl_str_mv 2000-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/23359
url http://sedici.unlp.edu.ar/handle/10915/23359
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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