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https://hdl.handle.net/1822/41423
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Campo DC | Valor | Idioma |
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dc.contributor.author | Pereira, Vítor Manuel Sá | por |
dc.contributor.author | Rocha, Miguel | por |
dc.contributor.author | Sousa, Pedro | por |
dc.date.accessioned | 2016-05-04T10:38:36Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Pereira, Vitor; Rocha, Miguel; Sousa, Pedro, Automated network resilience optimization using computational intelligence methods. In Paulo Novais, David Camacho, Cesar Analide, Amal El Fallah Seghrouchni, Costin Badica, Studies in Computational Intelligence, Vol. 616: Intelligent Distributed Computing IX, Springer International Publishing, 2016. ISBN: 978-3-319-25015-1, 485-495 | - |
dc.identifier.isbn | 978-3-319-25015-1 | por |
dc.identifier.issn | 1860-949X | por |
dc.identifier.uri | https://hdl.handle.net/1822/41423 | - |
dc.description.abstract | This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods. | por |
dc.description.sponsorship | This work has been partially supported by FCT - Fundação para a Ciência e Tecnologia Portugal in the scope of the project: UID/CEC/00319/2013. | por |
dc.language.iso | eng | por |
dc.publisher | Springer Verlag | por |
dc.relation | info:eu-repo/grantAgreement/FCT/5876/147280/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/5876/147280/PT | - |
dc.rights | restrictedAccess | por |
dc.title | Automated network resilience optimization using computational intelligence methods | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | - |
dc.relation.publisherversion | http://link.springer.com/book/10.1007/978-3-319-25017-5 | por |
dc.comments | CEB24452 | por |
sdum.publicationstatus | published | - |
oaire.citationStartPage | 485 | por |
oaire.citationEndPage | 495 | por |
oaire.citationTitle | Studies in Computational Intelligence | por |
oaire.citationVolume | 616 | por |
dc.date.updated | 2016-04-09T01:28:50Z | - |
dc.identifier.doi | 10.1007/978-3-319-25017-5_46 | por |
dc.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | - |
sdum.journal | Studies in Computational Intelligence | por |
sdum.conferencePublication | INTELLIGENT DISTRIBUTED COMPUTING IX, IDC'2015 | por |
sdum.bookTitle | Studies in Computational Intelligence | por |
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