2020
DOI: 10.1109/tnsm.2019.2934316
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CAPEST: Offloading Network Capacity and Available Bandwidth Estimation to Programmable Data Planes

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Cited by 20 publications
(9 citation statements)
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References 35 publications
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“…This work uses no machine learning technologies, and it focuses on estimating bandwidth of single node rather than whole network. Reference [17] proposes a passive capacity and available bandwidth measurement method for the data plane, employing packet dispersion and autocorrelation.…”
Section: Related Workmentioning
confidence: 99%
“…This work uses no machine learning technologies, and it focuses on estimating bandwidth of single node rather than whole network. Reference [17] proposes a passive capacity and available bandwidth measurement method for the data plane, employing packet dispersion and autocorrelation.…”
Section: Related Workmentioning
confidence: 99%
“…Literature regarding packet pair dispersion and capacity estimation is extensive. As of today many schemes for the narrow link capacity estimation have been proposed [1]- [4]. Most models, either based on active probing or passive measurements, measure the dispersion between packet pairs or packet trains.…”
Section: Related Workmentioning
confidence: 99%
“…Most models, either based on active probing or passive measurements, measure the dispersion between packet pairs or packet trains. Packet pairs dispersion has been proven to be a noisy measurement [2], [4], [6]. The effort of most works in this area have been focusing on signal processing and de-noising of the intern-packet rate distribution derived from packet pairs dispersion.…”
Section: Related Workmentioning
confidence: 99%
“…• Five papers in top-tier SBC, IEEE and ACM conferences/journals (first author) [da Costa Filho et al 2016b, da Costa Filho et al 2016a, da Costa Filho et al 2018a, da Costa Filho et al 2018b, da Costa Filho et al 2020]. • Five papers in conferences/journals (co-author) [Marques et al 2019, Kagami et al 2019, Roesler et al 2018, Lautenschläger et al 2016, Lazzari et al 2017]. • Ph.D. defense awarded with Honors Thesis High Distinction.…”
Section: Research Accomplishments and Contributionsmentioning
confidence: 99%