Multiobjective multicast routing with Ant Colony Optimization

Autores
Pinto, Diego; Barán, Benjamín
Año de publicación
2006
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
This work presents a multiobjective algorithm for multicast traffic engineering. The proposed algorithm is a new version of MultiObjective Ant Colony System (MOACS), based on Ant Colony Optimization (ACO). The proposed MOACS simultaneously optimizes the maximum link utilization, the cost of the multicast tree, the averages delay and the maximum endtoend delay. In this way, a set of optimal solutions, known as Pareto set is calculated in only one run of the algorithm, without a priori restrictions. Experimental results obtained with the proposed MOACS were compared to a recently published Multiobjective Multicast Algorithm (MMA), showing a promising performance advantage for multicast traffic engineering.
5th IFIP International Conference on Network Control & Engineering for QoS, Security and Mobility
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
MultiObjective Ant Colony System (MOACS)
Multiobjective Multicast Algorithm (MMA)
Network Protocols
Internet (e.g., TCP/IP)
Algorithms
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:10915/24116
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/24116
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Multiobjective multicast routing with Ant Colony OptimizationPinto, DiegoBarán, BenjamínCiencias InformáticasMultiObjective Ant Colony System (MOACS)Multiobjective Multicast Algorithm (MMA)Network ProtocolsInternet (e.g., TCP/IP)AlgorithmsThis work presents a multiobjective algorithm for multicast traffic engineering. The proposed algorithm is a new version of MultiObjective Ant Colony System (MOACS), based on Ant Colony Optimization (ACO). The proposed MOACS simultaneously optimizes the maximum link utilization, the cost of the multicast tree, the averages delay and the maximum endtoend delay. In this way, a set of optimal solutions, known as Pareto set is calculated in only one run of the algorithm, without a priori restrictions. Experimental results obtained with the proposed MOACS were compared to a recently published Multiobjective Multicast Algorithm (MMA), showing a promising performance advantage for multicast traffic engineering.5th IFIP International Conference on Network Control & Engineering for QoS, Security and MobilityRed de Universidades con Carreras en Informática (RedUNCI)2006-08info: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/10915/24116enginfo:eu-repo/semantics/altIdentifier/isbn/0-387-34825-5info: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:UNLP2025-09-03T10:28:30Zoai:sedici.unlp.edu.ar:10915/24116Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:28:30.832SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Multiobjective multicast routing with Ant Colony Optimization
title Multiobjective multicast routing with Ant Colony Optimization
spellingShingle Multiobjective multicast routing with Ant Colony Optimization
Pinto, Diego
Ciencias Informáticas
MultiObjective Ant Colony System (MOACS)
Multiobjective Multicast Algorithm (MMA)
Network Protocols
Internet (e.g., TCP/IP)
Algorithms
title_short Multiobjective multicast routing with Ant Colony Optimization
title_full Multiobjective multicast routing with Ant Colony Optimization
title_fullStr Multiobjective multicast routing with Ant Colony Optimization
title_full_unstemmed Multiobjective multicast routing with Ant Colony Optimization
title_sort Multiobjective multicast routing with Ant Colony Optimization
dc.creator.none.fl_str_mv Pinto, Diego
Barán, Benjamín
author Pinto, Diego
author_facet Pinto, Diego
Barán, Benjamín
author_role author
author2 Barán, Benjamín
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
MultiObjective Ant Colony System (MOACS)
Multiobjective Multicast Algorithm (MMA)
Network Protocols
Internet (e.g., TCP/IP)
Algorithms
topic Ciencias Informáticas
MultiObjective Ant Colony System (MOACS)
Multiobjective Multicast Algorithm (MMA)
Network Protocols
Internet (e.g., TCP/IP)
Algorithms
dc.description.none.fl_txt_mv This work presents a multiobjective algorithm for multicast traffic engineering. The proposed algorithm is a new version of MultiObjective Ant Colony System (MOACS), based on Ant Colony Optimization (ACO). The proposed MOACS simultaneously optimizes the maximum link utilization, the cost of the multicast tree, the averages delay and the maximum endtoend delay. In this way, a set of optimal solutions, known as Pareto set is calculated in only one run of the algorithm, without a priori restrictions. Experimental results obtained with the proposed MOACS were compared to a recently published Multiobjective Multicast Algorithm (MMA), showing a promising performance advantage for multicast traffic engineering.
5th IFIP International Conference on Network Control & Engineering for QoS, Security and Mobility
Red de Universidades con Carreras en Informática (RedUNCI)
description This work presents a multiobjective algorithm for multicast traffic engineering. The proposed algorithm is a new version of MultiObjective Ant Colony System (MOACS), based on Ant Colony Optimization (ACO). The proposed MOACS simultaneously optimizes the maximum link utilization, the cost of the multicast tree, the averages delay and the maximum endtoend delay. In this way, a set of optimal solutions, known as Pareto set is calculated in only one run of the algorithm, without a priori restrictions. Experimental results obtained with the proposed MOACS were compared to a recently published Multiobjective Multicast Algorithm (MMA), showing a promising performance advantage for multicast traffic engineering.
publishDate 2006
dc.date.none.fl_str_mv 2006-08
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/10915/24116
url http://sedici.unlp.edu.ar/handle/10915/24116
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/0-387-34825-5
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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