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Finding Correlation and Predicting System Behavior in Large IT Infrastructure
Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology.
2014 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Modern IT development infrastructure has a large number of components that must be monitored, for instance servers and network components. Various system-metrics (build time, CPU utilization, queries time etc.) are gathered to monitor system performance. In practice, it is extremely difficult for a system administrator to observe a correlation between several systemmetrics and predict a target system-metric based on highly correlated system-metrics without machine learning support.

The experiments were performed on development logs at Ericsson. There were many system-metrics available in the system. Our goal is use machine learning techniques to find correlation between buildtime and other system-metrics and predict its trends in the future.

Place, publisher, year, edition, pages
2014. , 48 p.
Keyword [en]
Correlation, Prediction, Time series, PCA, Automation
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:liu:diva-112850ISRN: LIU-IDA/ LITH-EX-A--13/024--SE, SaSOAI: oai:DiVA.org:liu-112850DiVA: diva2:772760
External cooperation
Ericsson AB
Subject / course
Master's programme in Computer Science
Available from: 2014-12-17 Created: 2014-12-17 Last updated: 2014-12-17Bibliographically approved

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fulltext(727 kB)174 downloads
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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
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  • en-US
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  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
  • html
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  • asciidoc
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