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Predicting SLA Conformance for Cluster-based Services
KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. SICS, Kista, Sweden.
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2017 (English)In: 2017 IFIP Networking Conference (IFIP NETWORKING) and Workshops, IEEE, 2017Conference paper, Published paper (Refereed)
Abstract [en]

The ability to predict conformance or violation for given Service-level Agreements (SLAs) is critical for service assurance. We demonstrate a prototype for real-time conformance prediction based on the concept of the capacity region, which abstracts the underlying ICT infrastructure with respect to the load it can carry for a given SLA. The capacity region is estimated through measurements and statistical learning. We demonstrate prediction for a key-value store (Voldemort) that runs on a server cluster located at KTH.

Place, publisher, year, edition, pages
IEEE, 2017.
Keywords [en]
Capacity Region, Feasible Region, Real-time Prediction, Statistical Learning, Service-level Agreement (SLA)
National Category
Social and Economic Geography
Identifiers
URN: urn:nbn:se:kth:diva-224115ISI: 000425452000050ISBN: 978-3-9018-8294-4 (print)OAI: oai:DiVA.org:kth-224115DiVA, id: diva2:1189522
Conference
IFIP Networking Conference (IFIP Networking),JUN 12-16, 2017, Stockholm, Sweden
Funder
VINNOVASwedish Research Council
Note

QC 20180312

Available from: 2018-03-12 Created: 2018-03-12 Last updated: 2018-03-12Bibliographically 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
  • rtf