Quality of service constrained routing optimization using evolutionary computation

Detalhes bibliográficos
Autor(a) principal: Rocha, Miguel
Data de Publicação: 2011
Outros Autores: Sousa, Pedro, Cortez, Paulo, Rio, Miguel
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/11983
Resumo: In this work, a novel optimization framework is proposed that allows the im- provement of Quality of Service levels in TCP/IP based networks, by configuring the routing weights of link-state protocols such as OSPF. Since this is a NP-hard problem, some algorithms from Evolutionary Computation were considered, work- ing over a mathematical model that allows the definition of flexible cost functions that can take into account several measures of the network behaviour, such as net- work congestion and end-to-end delays. A number of experiments were performed, over a large set of network topologies, where Evolutionary Algorithms (EAs), Dif- ferential Evolution, local search methods and common heuristics were compared. EAs make the most promising alternative leading to solutions with an effective net- work performance, even under unfavourable scenarios. A number of state of the art multiobjective optimization algorithms were also tested, but the proposed EAs still hold as the most consistent method for network optimization.
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spelling Quality of service constrained routing optimization using evolutionary computationTraffic engineeringQuality of serviceTCP/IP networksOSPFEvolutionary algorithmsScience & TechnologyIn this work, a novel optimization framework is proposed that allows the im- provement of Quality of Service levels in TCP/IP based networks, by configuring the routing weights of link-state protocols such as OSPF. Since this is a NP-hard problem, some algorithms from Evolutionary Computation were considered, work- ing over a mathematical model that allows the definition of flexible cost functions that can take into account several measures of the network behaviour, such as net- work congestion and end-to-end delays. A number of experiments were performed, over a large set of network topologies, where Evolutionary Algorithms (EAs), Dif- ferential Evolution, local search methods and common heuristics were compared. EAs make the most promising alternative leading to solutions with an effective net- work performance, even under unfavourable scenarios. A number of state of the art multiobjective optimization algorithms were also tested, but the proposed EAs still hold as the most consistent method for network optimization.Fundação para a Ciência e a Tecnologia (FCT) - Contract CONC-REEQ/443/2001British Council Portugal - B-53/05 grantPortuguese National Conference of Rectors (CRUP)Nuffield Foundation - NAL/001136/A grantEngineering and Physical Sciences Research Council - EP/522885 grantProject SeARCH (Services and Advanced Research Computing with HTC/HPC clusters)Elsevier Science BVUniversidade do MinhoRocha, MiguelSousa, PedroCortez, PauloRio, Miguel20112011-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/11983eng1568-494610.1016/j.asoc.2009.11.026http://dx.doi.org/10.1016/j.asoc.2009.11.026info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T11:59:07Zoai:repositorium.sdum.uminho.pt:1822/11983Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:48:52.849969Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Quality of service constrained routing optimization using evolutionary computation
title Quality of service constrained routing optimization using evolutionary computation
spellingShingle Quality of service constrained routing optimization using evolutionary computation
Rocha, Miguel
Traffic engineering
Quality of service
TCP/IP networks
OSPF
Evolutionary algorithms
Science & Technology
title_short Quality of service constrained routing optimization using evolutionary computation
title_full Quality of service constrained routing optimization using evolutionary computation
title_fullStr Quality of service constrained routing optimization using evolutionary computation
title_full_unstemmed Quality of service constrained routing optimization using evolutionary computation
title_sort Quality of service constrained routing optimization using evolutionary computation
author Rocha, Miguel
author_facet Rocha, Miguel
Sousa, Pedro
Cortez, Paulo
Rio, Miguel
author_role author
author2 Sousa, Pedro
Cortez, Paulo
Rio, Miguel
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Rocha, Miguel
Sousa, Pedro
Cortez, Paulo
Rio, Miguel
dc.subject.por.fl_str_mv Traffic engineering
Quality of service
TCP/IP networks
OSPF
Evolutionary algorithms
Science & Technology
topic Traffic engineering
Quality of service
TCP/IP networks
OSPF
Evolutionary algorithms
Science & Technology
description In this work, a novel optimization framework is proposed that allows the im- provement of Quality of Service levels in TCP/IP based networks, by configuring the routing weights of link-state protocols such as OSPF. Since this is a NP-hard problem, some algorithms from Evolutionary Computation were considered, work- ing over a mathematical model that allows the definition of flexible cost functions that can take into account several measures of the network behaviour, such as net- work congestion and end-to-end delays. A number of experiments were performed, over a large set of network topologies, where Evolutionary Algorithms (EAs), Dif- ferential Evolution, local search methods and common heuristics were compared. EAs make the most promising alternative leading to solutions with an effective net- work performance, even under unfavourable scenarios. A number of state of the art multiobjective optimization algorithms were also tested, but the proposed EAs still hold as the most consistent method for network optimization.
publishDate 2011
dc.date.none.fl_str_mv 2011
2011-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/11983
url http://hdl.handle.net/1822/11983
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1568-4946
10.1016/j.asoc.2009.11.026
http://dx.doi.org/10.1016/j.asoc.2009.11.026
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eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv Elsevier Science BV
publisher.none.fl_str_mv Elsevier Science BV
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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