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Abstract

International audience; The study of round-trip time (RTT) measurements on the Internet is of particular importance for improving real-time applications, enforcing QoS with traffic engineering, or detecting unexpected network conditions. On large timescales, from 1 hour to several days, RTT measurements exhibit characteristic patterns due to inter and intra-AS routing changes and traffic engineering, in addition to link congestion. We propose the use of a nonparametric Bayesian method to fully estimate HMM parameters from delay observations, including the number of states. We validate the model through three applications: the clustering of RIPE Atlas measurements, the detection of significant delay changes, and the reduction of the monitoring cost in routing overlays using Markov decision processes.


Original document

The different versions of the original document can be found in:

http://dx.doi.org/10.1109/infcomw.2019.8845296
https://hal.archives-ouvertes.fr/hal-02300968,
https://hal.archives-ouvertes.fr/hal-02300968/document,
https://academic.microsoft.com/#/detail/2976704435
https://hal.archives-ouvertes.fr/hal-02300968/document,
https://hal.archives-ouvertes.fr/hal-02300968/file/INFOCOM_2019___Abstract.pdf
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Document information

Published on 01/01/2019

Volume 2019, 2019
DOI: 10.1109/infcomw.2019.8845296
Licence: CC BY-NC-SA license

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