Distributed Internet Paths Performance Analysis through Machine Learning

Abstract : Internet path changes are frequently linked to path inflation and performance degradation; therefore, predicting their occurrence is highly relevant for performance monitoring and dynamic traffic engineering. In this paper we showcase DisNETPerf and NETPerfTrace, two different and complementary tools for distributed Internet paths performance analysis, using machine learning models.
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Conference papers
Demonstrations of the Network Traffic Measurement and Analysis Conference (TMA) 2018, Jun 2018, Vienne, Austria. 〈http://tma.ifip.org/2018/〉
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https://hal.inria.fr/hal-01883815
Contributor : Sarah Wassermann <>
Submitted on : Friday, September 28, 2018 - 5:31:46 PM
Last modification on : Friday, October 5, 2018 - 4:23:20 PM

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Sarah Wassermann, Pedro Casas. Distributed Internet Paths Performance Analysis through Machine Learning. Demonstrations of the Network Traffic Measurement and Analysis Conference (TMA) 2018, Jun 2018, Vienne, Austria. 〈http://tma.ifip.org/2018/〉. 〈hal-01883815〉

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