A Clustering Approach To Reduce The Available Bandwidth Estimation Error

The 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 natu...

Full description

Autores:
Guerrero, Cesar D.
Salcedo Morillo, Dixon David
Lamos, Henry
Tipo de recurso:
Article of journal
Fecha de publicación:
2013
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
spa
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/812
Acceso en línea:
https://hdl.handle.net/11323/812
http://doi.org/10.1109/TLA.2013.6568835
https://repositorio.cuc.edu.co/
Palabra clave:
Available Bandwidth Estimation
Clustering
K-Means
Traceband
Rights
openAccess
License
Atribución – No comercial – Compartir igual
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dc.title.eng.fl_str_mv A Clustering Approach To Reduce The Available Bandwidth Estimation Error
title A Clustering Approach To Reduce The Available Bandwidth Estimation Error
spellingShingle A Clustering Approach To Reduce The Available Bandwidth Estimation Error
Available Bandwidth Estimation
Clustering
K-Means
Traceband
title_short A Clustering Approach To Reduce The Available Bandwidth Estimation Error
title_full A Clustering Approach To Reduce The Available Bandwidth Estimation Error
title_fullStr A Clustering Approach To Reduce The Available Bandwidth Estimation Error
title_full_unstemmed A Clustering Approach To Reduce The Available Bandwidth Estimation Error
title_sort A Clustering Approach To Reduce The Available Bandwidth Estimation Error
dc.creator.fl_str_mv Guerrero, Cesar D.
Salcedo Morillo, Dixon David
Lamos, Henry
dc.contributor.author.spa.fl_str_mv Guerrero, Cesar D.
Salcedo Morillo, Dixon David
Lamos, Henry
dc.subject.eng.fl_str_mv Available Bandwidth Estimation
Clustering
K-Means
Traceband
topic Available Bandwidth Estimation
Clustering
K-Means
Traceband
description The 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.
publishDate 2013
dc.date.issued.none.fl_str_mv 2013-05-03
dc.date.accessioned.none.fl_str_mv 2018-11-09T18:28:47Z
dc.date.available.none.fl_str_mv 2018-11-09T18:28:47Z
dc.type.spa.fl_str_mv Artículo de revista
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.content.spa.fl_str_mv Text
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.issn.spa.fl_str_mv 15480992
dc.identifier.uri.spa.fl_str_mv https://hdl.handle.net/11323/812
dc.identifier.doi.spa.fl_str_mv http://doi.org/10.1109/TLA.2013.6568835
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co/
identifier_str_mv 15480992
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/812
http://doi.org/10.1109/TLA.2013.6568835
https://repositorio.cuc.edu.co/
dc.language.iso.none.fl_str_mv spa
language spa
dc.rights.spa.fl_str_mv Atribución – No comercial – Compartir igual
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
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rights_invalid_str_mv Atribución – No comercial – Compartir igual
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.publisher.spa.fl_str_mv IEEE
institution Corporación Universidad de la Costa
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spelling Guerrero, Cesar D.Salcedo Morillo, Dixon DavidLamos, Henry2018-11-09T18:28:47Z2018-11-09T18:28:47Z2013-05-0315480992https://hdl.handle.net/11323/812http://doi.org/10.1109/TLA.2013.6568835Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/The 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.Guerrero, Cesar D.-9d747112-630a-4a1c-ab0e-0923bd2f4e8e-0Salcedo Morillo, Dixon David-0000-0002-3762-8462-600Lamos, Henry-32149a59-e685-4af7-82cd-fc2eba718691-0spaIEEEAtribución – No comercial – Compartir igualinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Available Bandwidth EstimationClusteringK-MeansTracebandA Clustering Approach To Reduce The Available Bandwidth Estimation ErrorArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionPublicationORIGINALA Clustering Approach to Reduce.pdfA Clustering Approach to Reduce.pdfapplication/pdf354421https://repositorio.cuc.edu.co/bitstreams/c755972b-c2ee-4021-a60f-01fb7a79bc3b/download5d0491972c2cc895d80100ad180fd927MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.cuc.edu.co/bitstreams/ed500d14-78da-40ec-a34f-d4de4df1f995/download8a4605be74aa9ea9d79846c1fba20a33MD52THUMBNAILA Clustering Approach to Reduce.pdf.jpgA Clustering Approach to Reduce.pdf.jpgimage/jpeg34866https://repositorio.cuc.edu.co/bitstreams/17ff29d4-dea3-435e-bce6-044a3f971c49/downloadcca1c43055af125dce8e7c5c4ccdc4cbMD54TEXTA Clustering Approach to Reduce.pdf.txtA Clustering Approach to Reduce.pdf.txttext/plain1110https://repositorio.cuc.edu.co/bitstreams/280bef42-0154-4821-97d7-1c7941fabaf8/download7e6e747537061e02545384a369d2296eMD5511323/812oai:repositorio.cuc.edu.co:11323/8122024-09-17 14:17:36.832open.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa CUCrepdigital@cuc.edu.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