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A Bayesian system for cloud performance diagnosis and prediction
Luleå tekniska universitet.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-3489-7429
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
Number of Authors: 4
2017 (English)In: Proceedings of the International Conference on Cloud Computing Technology and Science, CloudCom, Piscataway, NJ: IEEE Computer Society, 2017, 371-374 p., 7830706Conference paper, (Refereed)
Abstract [en]

The stochastic nature of the cloud systems makes cloud quality of service (QoS) performance diagnosis and prediction a challenging task. A plethora of factors including virtual machine types, data centre regions, CPU types, time-of-the-day, and day-of-the-week contribute to the variability of the cloud QoS. The state-of-the-art methods for cloud performance diagnosis do not capture and model complex and uncertain inter-dependencies between these factors for efficient cloud QoS diagnosis and prediction. This paper presents ALPINE, a proof-of-concept system based on Bayesian networks. Using a real-life dataset, we demonstrate that ALPINE can be utilised for efficient cloud QoS diagnosis and prediction under stochastic cloud conditions

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Computer Society, 2017. 371-374 p., 7830706
Series
International Conference on Cloud Computing Technology and Science, ISSN 2330-2194
National Category
Media and Communication Technology
Research subject
Mobile and Pervasive Computing
Identifiers
URN: urn:nbn:se:ltu:diva-62202DOI: 10.1109/CloudCom.2016.0065ISI: 000398536300049Scopus ID: 2-s2.0-85013025438ISBN: 9781509014453 (electronic)OAI: oai:DiVA.org:ltu-62202DiVA: diva2:1077597
Conference
8th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2016, Luxembourg, 12-15 December 2016
Available from: 2017-02-28 Created: 2017-02-28 Last updated: 2017-04-28Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
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