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Automated diagnostic of virtualized service performance degradation
Ericsson Research, Sweden.
Uppsala University, Sweden.
Ericsson Research, Sweden.
Ericsson Research, Sweden.
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2018 (English)In: IEEE/IFIP Network Operations and Management Symposium: Cognitive Management in a Cyber World, NOMS 2018, 2018Conference paper, Published paper (Refereed)
Abstract [en]

Service assurance for cloud applications is a challenging task and is an active area of research for academia and industry. One promising approach is to utilize machine learning for service quality prediction and fault detection so that suitable mitigation actions can be executed. In our previous work, we have shown how to predict service-level metrics in real-time just from operational data gathered at the server side. This gives the service provider early indications on whether the platform can support the current load demand. This paper provides the logical next step where we extend our work by proposing an automated detection and diagnostic capability for the performance faults manifesting themselves in cloud and datacenter environments. This is a crucial task to maintain the smooth operation of running services and minimizing downtime. We demonstrate the effectiveness of our approach which exploits the interpretative capabilities of Self- Organizing Maps (SOMs) to automatically detect and localize different performance faults for cloud services.

Place, publisher, year, edition, pages
2018.
Keywords [en]
Fault detection, Fault localization, Machine learning, Service quality, System statistics, Video streaming, Conformal mapping, Learning systems, Quality of service, Self organizing maps, Automated detection, Automated diagnostics, Cloud applications, Self organizing maps(soms), Virtualized services
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:ri:diva-37294DOI: 10.1109/NOMS.2018.8406234Scopus ID: 2-s2.0-85050672220ISBN: 9781538634165 (print)OAI: oai:DiVA.org:ri-37294DiVA, id: diva2:1280232
Conference
2018 IEEE/IFIP Network Operations and Management Symposium, NOMS 2018, 23 April 2018 through 27 April 2018
Available from: 2019-01-18 Created: 2019-01-18 Last updated: 2019-03-28Bibliographically 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
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