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Statistical analysis and prioritisation of alarms in mobile networks
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
Data Ductus.
2009 (English)In: International Journal of Business Intelligence and Data Mining, ISSN 1743-8195, Vol. 4, no 1, 4-21 p.Article in journal (Refereed) Published
Abstract [en]

Telecom Service Providers are faced with an overwhelming flow of alarms, which makes good alarm classification and prioritization very important. This paper first provides statistical analysis of data collected from a real-world alarm flow and then presents a quantitative characterization of the alarm situation. Using data from the trouble ticketing system as a reference, we examine the relationship between mechanical classification of alarms and the human perception of them.Using this knowledge of alarm flow properties and trouble ticketing information, we suggest a neural network-based approach for alarm classification. Tests using live data show that our prototype assigns the same severity as a human expert in 50% of all cases, compared to 17% for a naive approach.

Place, publisher, year, edition, pages
2009. Vol. 4, no 1, 4-21 p.
National Category
Embedded Systems Media and Communication Technology
Research subject
Embedded System; Mobile and Pervasive Computing
Identifiers
URN: urn:nbn:se:ltu:diva-7862DOI: 10.1504/IJBIDM.2009.025408Local ID: 649e4ab0-c323-11dd-a054-000ea68e967bOAI: oai:DiVA.org:ltu-7862DiVA: diva2:980752
Note
Validerad; 2009; 20081206 (leijon)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • en-GB
  • en-US
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  • nn-NB
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Output format
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