A Cascade of Consequences: Improving an Accident Analysis Method by Learning from a Real Life Telecommunications Accident

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Abstract

Telecommunications networks are vital enablers of modern society. Large accidents in these networks that cause their unavailability can therefore have a severe impact on the functioning of society. Learning from these accidents can help prevent them and thus make our society more resilient. In this paper, we present an accident analysis method (TRAM) which we have developed by extending the AcciMap method and we report on its application to analyse a severe accident in a telecommunications network. We validate notation for representing and breaking positive feedback loops in a network breakdown, and we suggest a method to enhance the prioritisation of recommendations derived from our analysis. Furthermore, our research reveals that splitting the analysis based on the expertise of the method’s participants negatively impacts the efficiency of the overall process.

Original languageEnglish
Title of host publicationProceedings of the 13th International Conference on Data Science, Technology and Applications, DATA 2024
EditorsElhadj Benkhelifa, Alfredo Cuzzocrea, Oleg Gusikhin, Slimane Hammoudi
PublisherSCITEPRESS
Pages62-70
Number of pages9
ISBN (Electronic)9789897587078
DOIs
Publication statusPublished - 2024
Event13th International Conference on Data Science, Technology and Applications, DATA 2024 - Dijon, France
Duration: 9 Jul 202411 Jul 2024
Conference number: 13

Conference

Conference13th International Conference on Data Science, Technology and Applications, DATA 2024
Abbreviated titleDATA 2024
Country/TerritoryFrance
CityDijon
Period9/07/2411/07/24

Keywords

  • Accident Analysis
  • Incident Analysis
  • Telecommunications

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