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Learning from Network Device Statistics
KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. Swedish Institute of Computer Science (RISE SICS) Kista Sweden.
KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
2017 (English)In: Journal of Network and Systems Management, ISSN 1064-7570, E-ISSN 1573-7705, Vol. 25, no 4, p. 672-698Article in journal (Refereed) Published
Abstract [en]

We estimate end-to-end service metrics from network device statistics. Our approach is based upon statistical, supervised learning, whereby the mapping from device-level to service-level metrics is learned from observations, i.e., through monitoring the system. The approach enables end-to-end performance prediction without requiring an explicit model of the system, which is different from traditional engineering techniques that use stochastic modeling and simulation. The fact that end-to-end service metrics can be estimated from local network statistics with good accuracy in the scenarios we consider suggests that service-level properties are "encoded" in network-level statistics. We show that the set of network statistics needed for estimation can be reduced to a set of measurements along the network path between client and service backend, with little loss in estimation accuracy. The reported work is largely experimental and its results have been obtained through testbed measurements from a video streaming service and a KV store over an OpenFlow network.

Place, publisher, year, edition, pages
SPRINGER , 2017. Vol. 25, no 4, p. 672-698
Keywords [en]
Network management, Machine learning, Statistical learning, Feature selection, End-to-end performance Prediction, Network analytics, OpenFlow
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-217759DOI: 10.1007/s10922-017-9426-zISI: 000414211400002Scopus ID: 2-s2.0-85029795404OAI: oai:DiVA.org:kth-217759DiVA, id: diva2:1158924
Note

QC 20171121

Available from: 2017-11-21 Created: 2017-11-21 Last updated: 2018-01-13Bibliographically approved

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Stadler, Rolf

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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