Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/211828
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dc.contributor.authorRongping Linen_US
dc.contributor.authorXingqiu Heen_US
dc.contributor.authorSheng Wangen_US
dc.contributor.authorShan Luoen_US
dc.contributor.authorYong Xiaoen_US
dc.contributor.authorXiaoning Zhangen_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T08:03:02Z-
dc.date.available2020-04-06T08:03:02Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/ACCESS.2017.2741222en_US
dc.identifier.urihttp://localhost/handle/Hannan/211828-
dc.descriptionen_US
dc.description.abstractAvailable bandwidth (AB) measurement technologies have been widely applied in evaluating the efficiency of the network communication. The performance of most existing AB measurement methods relies on the quality of the input data, which inevitably contains noises during the measurement. These noises can be multisourcing from end-to-end packet transmission and measuring, and in many practical situations, are nonnegligible compared with the value of measuring data. This paper focuses on estimating the end-to-end AB in terms of packet delays from sampled data that is contaminated by noises. We propose a novel algorithm, referred to as the adaptive-threshold algorithm, that can estimate and adaptively adjust a threshold value to separate the packets affected by the queueing delays from the rest of the packets to further improve the accuracy of AB measurement. A laboratory network-based simulation has been presented to evaluate the performance of our proposed algorithm. Numerical results demonstrate that the proposed algorithm can significantly improve the accuracy of the measurement and the estimated AB is within 10&x0025; difference from the true AB.en_US
dc.format.extent22584,en_US
dc.format.extent22589en_US
dc.publisherIEEEen_US
dc.relation.haspart8013024.pdfen_US
dc.titleEstimating End-to-End Available Bandwidth With Noisesen_US
dc.typeArticleen_US
dc.journal.volume5en_US
Appears in Collections:2017

Files in This Item:
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8013024.pdf9.34 MBAdobe PDF
Full metadata record
DC FieldValueLanguage
dc.contributor.authorRongping Linen_US
dc.contributor.authorXingqiu Heen_US
dc.contributor.authorSheng Wangen_US
dc.contributor.authorShan Luoen_US
dc.contributor.authorYong Xiaoen_US
dc.contributor.authorXiaoning Zhangen_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T08:03:02Z-
dc.date.available2020-04-06T08:03:02Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/ACCESS.2017.2741222en_US
dc.identifier.urihttp://localhost/handle/Hannan/211828-
dc.descriptionen_US
dc.description.abstractAvailable bandwidth (AB) measurement technologies have been widely applied in evaluating the efficiency of the network communication. The performance of most existing AB measurement methods relies on the quality of the input data, which inevitably contains noises during the measurement. These noises can be multisourcing from end-to-end packet transmission and measuring, and in many practical situations, are nonnegligible compared with the value of measuring data. This paper focuses on estimating the end-to-end AB in terms of packet delays from sampled data that is contaminated by noises. We propose a novel algorithm, referred to as the adaptive-threshold algorithm, that can estimate and adaptively adjust a threshold value to separate the packets affected by the queueing delays from the rest of the packets to further improve the accuracy of AB measurement. A laboratory network-based simulation has been presented to evaluate the performance of our proposed algorithm. Numerical results demonstrate that the proposed algorithm can significantly improve the accuracy of the measurement and the estimated AB is within 10&x0025; difference from the true AB.en_US
dc.format.extent22584,en_US
dc.format.extent22589en_US
dc.publisherIEEEen_US
dc.relation.haspart8013024.pdfen_US
dc.titleEstimating End-to-End Available Bandwidth With Noisesen_US
dc.typeArticleen_US
dc.journal.volume5en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
8013024.pdf9.34 MBAdobe PDF
Full metadata record
DC FieldValueLanguage
dc.contributor.authorRongping Linen_US
dc.contributor.authorXingqiu Heen_US
dc.contributor.authorSheng Wangen_US
dc.contributor.authorShan Luoen_US
dc.contributor.authorYong Xiaoen_US
dc.contributor.authorXiaoning Zhangen_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T08:03:02Z-
dc.date.available2020-04-06T08:03:02Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/ACCESS.2017.2741222en_US
dc.identifier.urihttp://localhost/handle/Hannan/211828-
dc.descriptionen_US
dc.description.abstractAvailable bandwidth (AB) measurement technologies have been widely applied in evaluating the efficiency of the network communication. The performance of most existing AB measurement methods relies on the quality of the input data, which inevitably contains noises during the measurement. These noises can be multisourcing from end-to-end packet transmission and measuring, and in many practical situations, are nonnegligible compared with the value of measuring data. This paper focuses on estimating the end-to-end AB in terms of packet delays from sampled data that is contaminated by noises. We propose a novel algorithm, referred to as the adaptive-threshold algorithm, that can estimate and adaptively adjust a threshold value to separate the packets affected by the queueing delays from the rest of the packets to further improve the accuracy of AB measurement. A laboratory network-based simulation has been presented to evaluate the performance of our proposed algorithm. Numerical results demonstrate that the proposed algorithm can significantly improve the accuracy of the measurement and the estimated AB is within 10&x0025; difference from the true AB.en_US
dc.format.extent22584,en_US
dc.format.extent22589en_US
dc.publisherIEEEen_US
dc.relation.haspart8013024.pdfen_US
dc.titleEstimating End-to-End Available Bandwidth With Noisesen_US
dc.typeArticleen_US
dc.journal.volume5en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
8013024.pdf9.34 MBAdobe PDF