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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.ORCID iD: 0000-0001-8561-7963
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0002-8681-9572
Number of Authors: 42017 (English)In: Proceedings of the International Conference on Cloud Computing Technology and Science, CloudCom, Piscataway, NJ: IEEE Computer Society, 2017, p. 371-374, article id 7830706Conference paper, Published 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. p. 371-374, article id 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, id: 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: 2018-06-28Bibliographically approved

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Mitra, KaranSaguna, SagunaÅhlund, Christer

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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
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  • asciidoc
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