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Real-time Detection of Performance Anomalies for Cloud Services
Umeå University, Faculty of Science and Technology, Department of Computing Science. (Distributed Systems)
Intel Labs Europe, Ireland.
Umeå University, Faculty of Science and Technology, Department of Computing Science.
2016 (English)In: 2016 IEEE/ACM 24th International Symposium on Quality of Service (IWQoS 2016), IEEE Communications Society, 2016, 164-165 p.Conference paper, Published paper (Refereed)
Abstract [en]

We propose two adaptive techniques for detecting anomalies in real-time service performance measurements. The techniques yielded low false alarm rates when evaluated on multiple time-series from the Yahoo! Webscope anomaly detection traces. 

Place, publisher, year, edition, pages
IEEE Communications Society, 2016. 164-165 p.
Keyword [en]
Anomaly Detection, Systems Performance, Cloud Computing, Quality of Service, Performance Anomalies, Cloud Services
National Category
Computer Systems
Research subject
Computer Systems
Identifiers
URN: urn:nbn:se:umu:diva-124477DOI: 10.1109/IWQoS.2016.7590412ISI: 000389832500027OAI: oai:DiVA.org:umu-124477DiVA: diva2:952471
Conference
IEEE/ACM 24th International Symposium on Quality of Service (IWQoS)
Projects
Cloud Control (C0590801)
Funder
Swedish Research Council, C0590801
Available from: 2016-08-14 Created: 2016-08-14 Last updated: 2017-01-16Bibliographically approved

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Ibidunmoye, OlumuyiwaElmroth, Erik
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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
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