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dc.creatorGuerrero, Cesar D.
dc.creatorSalcedo Morillo, Dixon David
dc.creatorLamos, Henry
dc.date.accessioned2018-11-09T18:28:47Z
dc.date.available2018-11-09T18:28:47Z
dc.date.issued2013-05-03
dc.identifier.issn15480992
dc.identifier.urihttp://hdl.handle.net/11323/812
dc.description.abstractThe estimation of the available bandwidth (AB) in an end-to-end manner can be used in several network applications to improve their performance. Several tools send pairs of packets from one end to the other and measure the packets' dispersion to infer the value of the AB. Given the fractal nature of Internet traffic, these measurements have significant errors that affect the accuracy of the estimation. This article presents the application of a clustering technique to reduce the estimation error of the available bandwidth in and end-to-end path. The clustering technique used is K-means which is applied to a tool called Traceband that is originally based on a Hidden Markov Model to perform the estimation. It is shown that using K-means in Traceband can improve its accuracy in 67.45% when the cross traffic is about 70% of the end-to-end capacity.spa
dc.language.isoOthereng
dc.publisherIEEEeng
dc.rightsAtribución – No comercial – Compartir igualeng
dc.subjectAvailable Bandwidth Estimationeng
dc.subjectClusteringeng
dc.subjectK-Meanseng
dc.subjectTracebandeng
dc.titleA Clustering Approach To Reduce The Available Bandwidth Estimation Erroreng
dc.typeArticleeng
dc.identifier.doihttp://doi.org/10.1109/TLA.2013.6568835


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