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dc.contributor.authorMijumbi, Rashid
dc.contributor.authorGorricho Moreno, Juan Luis
dc.contributor.authorSerrat Fernández, Juan
dc.contributor.authorClaeys, Maxim
dc.contributor.authorDe Turck, Filip
dc.contributor.authorLatré, Steven
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica
dc.date.accessioned2015-01-29T11:38:57Z
dc.date.available2015-01-29T11:38:57Z
dc.date.created2014
dc.date.issued2014
dc.identifier.citationMijumbi, R. [et al.]. Design and evaluation of learning algorithms for dynamic resource management in virtual networks. A: IEEE/IFIP Network Operations and management Symposium. "NOMS 2014: 2014 IEEE/IFIP Network Operations and Management Symposium : Krakow, Poland, 5-9 May 2014". Krakow: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 1-9.
dc.identifier.isbn978-1-4799-0913-1
dc.identifier.urihttp://hdl.handle.net/2117/26154
dc.description.abstractNetwork virtualisation is considerably gaining attention as a solution to ossification of the Internet. However, the success of network virtualisation will depend in part on how efficiently the virtual networks utilise substrate network resources. In this paper, we propose a machine learning-based approach to virtual network resource management. We propose to model the substrate network as a decentralised system and introduce a learning algorithm in each substrate node and substrate link, providing self-organization capabilities. We propose a multiagent learning algorithm that carries out the substrate network resource management in a coordinated and decentralised way. The task of these agents is to use evaluative feedback to learn an optimal policy so as to dynamically allocate network resources to virtual nodes and links. The agents ensure that while the virtual networks have the resources they need at any given time, only the required resources are reserved for this purpose. Simulations show that our dynamic approach significantly improves the virtual network acceptance ratio and the maximum number of accepted virtual network requests at any time while ensuring that virtual network quality of service requirements such as packet drop rate and virtual link delay are not affected.
dc.format.extent9 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors::Serveis telemàtics i de comunicació multimèdia
dc.subject.lcshVirtual computer systems
dc.titleDesign and evaluation of learning algorithms for dynamic resource management in virtual networks
dc.typeConference lecture
dc.subject.lemacSistemes virtuals (Informàtica)
dc.contributor.groupUniversitat Politècnica de Catalunya. MAPS - Management, Pricing and Services in Next Generation Networks
dc.identifier.doi10.1109/NOMS.2014.6838258
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
drac.iddocument14885195
dc.description.versionPostprint (author’s final draft)
upcommons.citation.authorMijumbi, R.; Gorricho, J.; Serrat, J.; Claeys, M.; De Turck, F.; Latré, S.
upcommons.citation.contributorIEEE/IFIP Network Operations and management Symposium
upcommons.citation.pubplaceKrakow
upcommons.citation.publishedtrue
upcommons.citation.publicationNameNOMS 2014: 2014 IEEE/IFIP Network Operations and Management Symposium : Krakow, Poland, 5-9 May 2014
upcommons.citation.startingPage1
upcommons.citation.endingPage9


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