Distributed Internet Paths Performance Analysis through Machine Learning - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2018

Distributed Internet Paths Performance Analysis through Machine Learning

Sarah Wassermann
  • Function : Author
  • PersonId : 1032980

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.
Fichier principal
Vignette du fichier
disnetperf_demo_tma18.pdf (359.77 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-01883815 , version 1 (28-09-2018)

Identifiers

  • HAL Id : hal-01883815 , version 1

Cite

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. ⟨hal-01883815⟩

Collections

INRIA INRIA2
121 View
260 Download

Share

Gmail Mastodon Facebook X LinkedIn More