Quality of service constrained routing optimization using evolutionary computation
| Main Author: | |
|---|---|
| Publication Date: | 2011 |
| Other Authors: | , , |
| Format: | Article |
| Language: | eng |
| Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Download full: | https://hdl.handle.net/1822/11983 |
Summary: | 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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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/pdfhttps://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:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-04-12T04:02:04Zoai:repositorium.sdum.uminho.pt:1822/11983Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T14:49:17.144735Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| 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 |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
| format |
article |
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publishedVersion |
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https://hdl.handle.net/1822/11983 |
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https://hdl.handle.net/1822/11983 |
| dc.language.iso.fl_str_mv |
eng |
| language |
eng |
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1568-4946 10.1016/j.asoc.2009.11.026 http://dx.doi.org/10.1016/j.asoc.2009.11.026 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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Elsevier Science BV |
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Elsevier Science BV |
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