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Telecom alarm prioritization using neural networks
Data Ductus Nord AB.
2008 (English)In: 22nd International Conference on Advanced Information Networking and Applications - Workshops: AINAW 2008, Los Alamitos, Calif: IEEE Communications Society, 2008, 1468-1473 p.Conference paper, Published paper (Refereed)
Abstract [en]

Telecom Service Providers are faced with an overwhelming flow of alarms. Network administrators need to judge which alarms to resolve in order to maintain the service quality. The problem is that it is hard to pick the most important alarms. Which alarms have the highest priority? A solution that automatically assigns priorities to alarms would increase the efficiency of Network Management Centers. We have prototyped a solution that uses neural networks to assign alarm priority. The neural network learns from network administrators by using the manually assigned priorities in trouble-tickets. Our tests are based on live-data from a large mobile service provider and we show that neural networks can learn to assign relevant priorities to 75% of the alarms.

Place, publisher, year, edition, pages
Los Alamitos, Calif: IEEE Communications Society, 2008. 1468-1473 p.
Series
International Conference on Advanced Information Networking and Applications. Proceedings, ISSN 1550-445X
National Category
Media and Communication Technology
Research subject
Mobile and Pervasive Computing
Identifiers
URN: urn:nbn:se:ltu:diva-28018DOI: 10.1109/WAINA.2008.105Local ID: 1aa45ff0-9cc6-11dc-97ff-000ea68e967bISBN: 978-0-7695-3096-3 (electronic)OAI: oai:DiVA.org:ltu-28018DiVA: diva2:1001211
Conference
International Conference on Advanced Information Networking and Applications Workshops : 25/03/2008 - 28/03/2008
Note
Validerad; 2008; 20071127 (stewal)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved

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Wallin, Stefan
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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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