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Using the Last-mile Model as a Distributed Scheme for Available Bandwidth Prediction

hal.structure.identifierAlgorithmics for computationally intensive applications over wide scale distributed platforms [CEPAGE]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorBEAUMONT, Olivier
hal.structure.identifierAlgorithmics for computationally intensive applications over wide scale distributed platforms [CEPAGE]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorEYRAUD-DUBOIS, Lionel
hal.structure.identifierAlgorithmics for computationally intensive applications over wide scale distributed platforms [CEPAGE]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorWON, Young
dc.contributor.editorSpringer
dc.date.accessioned2024-04-15T09:47:31Z
dc.date.available2024-04-15T09:47:31Z
dc.date.issued2011
dc.date.conference2011-09
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/198103
dc.description.abstractEnSeveral Network Coordinate Systems have been proposed to predict unknown network distances between a large number of Internet nodes by using only a small number of measurements. These systems focus on predicting latency, and they are not adapted to the prediction of available bandwidth. But end-to-end path available bandwidth is an important metric for the performance optimisation in many high throughput distributed applications, such as video streaming and le sharing networks. In this paper, we propose to perform available bandwidth prediction with the last-mile model, in which each node is characterised by its incoming and outgoing capacities. This model has been used in several theoretical works for distributed applications. We design decentralised heuristics to compute the capacities of each node so as to minimise the prediction error. We show that our algorithms can achieve a competitive accuracy even with asymmetric and erroneous end-to-end measurement datasets. A comparison with existing models (Vivaldi, Sequoia, PathGuru, DMF) is provided. Simulation results also show that our heuristics can provide good quality predictions even when using a very small number of measurements.
dc.description.sponsorshipSimulation extrêmement extensible avec SimGrid - ANR-08-SEGI-0022
dc.language.isoen
dc.title.enUsing the Last-mile Model as a Distributed Scheme for Available Bandwidth Prediction
dc.typeCommunication dans un congrès
dc.subject.halInformatique [cs]/Calcul parallèle, distribué et partagé [cs.DC]
bordeaux.hal.laboratoriesLaboratoire Bordelais de Recherche en Informatique (LaBRI) - UMR 5800*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.conference.titleEuroPar 2011
bordeaux.countryFR
bordeaux.conference.cityBordeaux
bordeaux.peerReviewedoui
hal.identifierinria-00588651
hal.version1
hal.invitednon
hal.proceedingsoui
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//inria-00588651v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2011&rft.au=BEAUMONT,%20Olivier&EYRAUD-DUBOIS,%20Lionel&WON,%20Young&rft.genre=unknown


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