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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, Computer Science. Data Ductus Nord AB, Skellefteå, Sweden.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
Data Ductus Nord AB, Skellefteå, Sweden.
2009 (English)In: International Journal of Business Intelligence and Data Mining, ISSN 1743-8195, Vol. 4, no 1, p. 4-21Article 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, p. 4-21
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, id: diva2:980752
Note

Validerad; 2009; 20081206 (leijon)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-01-10Bibliographically approved

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CiteExportLink to record
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