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dc.contributor.authorHernandez Benet, Cristian
dc.contributor.authorKassler, Andreas
dc.contributor.authorZola, Enrica Valeria
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica
dc.date.accessioned2017-04-03T12:14:58Z
dc.date.available2017-04-03T12:14:58Z
dc.date.issued2016-10-24
dc.identifier.citationHernandez Benet, C., Kassler, A.J., Zola, E. Predicting expected TCP throughput using genetic algorithm. "Computer networks", 24 Octubre 2016, vol. 108, p. 307-322.
dc.identifier.issn1389-1286
dc.identifier.urihttp://hdl.handle.net/2117/103219
dc.description.abstractPredicting the expected throughput of TCP is important for several aspects such as e.g. determining handover criteria for future multihomed mobile nodes or determining the expected throughput of a given MPTCP subflow for load-balancing reasons. However, this is challenging due to time varying behavior of the underlying network characteristics. In this paper, we present a genetic-algorithm-based prediction model for estimating TCP throughput values. Our approach tries to find the best matching combination of mathematical functions that approximate a given time series that accounts for the TCP throughput samples using genetic algorithm. Based on collected historical datapoints about measured TCP throughput samples, our algorithm estimates expected throughput over time. We evaluate the quality of the prediction using different selection and diversity strategies for creating new chromosomes. Also, we explore the use of different fitness functions in order to evaluate the goodness of a chromosome. The goal is to show how different tuning on the genetic algorithm may have an impact on the prediction. Using extensive simulations over several TCP throughput traces, we find that the genetic algorithm successfully finds reasonable matching mathematical functions that allow to describe the TCP sampled throughput values with good fidelity. We also explore the effectiveness of predicting time series throughput samples for a given prediction horizon and estimate the prediction error and confidence.
dc.format.extent16 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació
dc.subject.lcshComputer algorithms
dc.subject.lcshCase-based reasoning
dc.subject.otherGenetic algorithm
dc.subject.otherTCP throughput
dc.subject.otherPrediction
dc.subject.otherIEEE 802.11
dc.titlePredicting expected TCP throughput using genetic algorithm
dc.typeArticle
dc.subject.lemacAlgorismes genètics
dc.subject.lemacRaonament basat en casos
dc.contributor.groupUniversitat Politècnica de Catalunya. GRXCA - Grup de Recerca en Xarxes de Comunicacions Cel·lulars i Ad-hoc
dc.identifier.doi10.1016/j.comnet.2016.08.027
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S1389128616302808
dc.rights.accessOpen Access
drac.iddocument18940238
dc.description.versionPostprint (author's final draft)
upcommons.citation.authorHernandez Benet, C., Kassler, A.J., Zola, E.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameComputer networks
upcommons.citation.volume108
upcommons.citation.startingPage307
upcommons.citation.endingPage322


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