Clustering of live network alarms using unsupervised statistical models - Archive ouverte HAL
Communication Dans Un Congrès Année : 2023

Clustering of live network alarms using unsupervised statistical models

Résumé

An unsupervised topology and time-based clustering model is proposed to regroup alarms according to their failure events. The different modes and settings of the model are assessed using topology and alarm-related data extracted from a live network as part of a field trial.
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Dates et versions

hal-04600192 , version 1 (04-06-2024)

Identifiants

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Diane Maillot-Tchofo, Ahmed Triki, Maxime Laye, John Puentes. Clustering of live network alarms using unsupervised statistical models. IET 49th European Conference on Optical Communications (ECOC 2023), The Institution of Engineering & Technology, Oct 2023, Glasgow, United Kingdom. pp.1246-1249, ⟨10.1049/icp.2023.2517⟩. ⟨hal-04600192⟩
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