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2020 | OriginalPaper | Buchkapitel

Space-Time Pattern Extraction in Alarm Logs for Network Diagnosis

verfasst von : Achille Salaün, Anne Bouillard, Marc-Olivier Buob

Erschienen in: Machine Learning for Networking

Verlag: Springer International Publishing

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Abstract

Increasing size and complexity of telecommunication networks make troubleshooting and network management more and more critical. As analyzing a log is cumbersome and time consuming, experts need tools helping them to quickly pinpoint the root cause when a problem arises. A structure called DIG-DAG able to store chain of alarms in a compact manner according to an input log has recently been proposed. Unfortunately, for large logs, this structure may be huge, and thus hardly readable for experts. To circumvent this problem, this paper proposes a framework allowing to query a DIG-DAG in order to extract patterns of interest, and a full methodology for end-to-end analysis of a log.

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Metadaten
Titel
Space-Time Pattern Extraction in Alarm Logs for Network Diagnosis
verfasst von
Achille Salaün
Anne Bouillard
Marc-Olivier Buob
Copyright-Jahr
2020
DOI
https://doi.org/10.1007/978-3-030-45778-5_10