An innovative machine learning approach to improve MPTCP performance

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dc.contributor.authorSilva, Fábio
dc.contributor.authorTogou, Mohammed Amine
dc.contributor.authorMuntean, Gabriel-Miro
dc.contributor.funderHorizon 2020en
dc.contributor.funderScience Foundation Irelanden
dc.date.accessioned2022-10-11T15:28:11Z
dc.date.available2022-10-11T15:28:11Z
dc.date.issued2020-07
dc.date.updated2022-10-11T15:14:51Z
dc.description.abstractThis paper presents, describes and evaluates the Machine Learning Performance Monitor (MLPM), an innovative Machine Learning (ML) approach to fore cast and extrapolate the performance of several network features (e.g., latency, throughput) in a Multipath TCP(MPTCP) subflow pool. MLPM uses linear regression to predict the performance of network features along with Artificial Neural Network linear classifier to choose the best subflow (i.e., network path) capable of delivering the best performance to a given set of the network features. Results show that MLPM delivers better performance in terms of throughput and latency compared to existing schemes as it improves the MPTCP scheduler performance.en
dc.description.sponsorshipScience Foundation Ireland (16/SP/3804; 12/RC/2289_P2)en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationSilva, F., Togou, M. A. and Muntean, G.-M. (2020) ‘An innovative machine learning approach to improve MPTCP performance', 2020 International Conference on High Performance Computing and Simulation (HPCS 2020), Barcelona, Spain, 20-24 July.en
dc.identifier.endpage8en
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/13764
dc.language.isoenen
dc.relation.projectinfo:eu-repo/grantAgreement/EC/H2020::IA/688503/EU/Networked Labs for Training in Sciences and Technologies for Information and Communication/NEWTONen
dc.relation.projectinfo:eu-repo/grantAgreement/EC/H2020::RIA/870610/EU/Opera co-creation for a social transformation/TRACTIONen
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/13/RC/2094/IE/Lero - the Irish Software Research Centre/en
dc.rights© 2020, the Authors.en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectLinear regressionen
dc.subjectMachine learningen
dc.subjectMultipath TCPen
dc.subjectSupervised learningen
dc.subjectNeural networken
dc.titleAn innovative machine learning approach to improve MPTCP performanceen
dc.typeConference itemen
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