"Improving Predictability of User-Affecting Metrics to Support Anomaly ..."

Vilc Queupe Rufino et al. (2020)

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DOI: 10.1109/ACCESS.2020.3028571

access: open

type: Journal Article

metadata version: 2020-12-31

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Vilc Queupe Rufino, Mateus Schulz Nogueira, Alberto Avritzer, Daniel Sadoc Menasché, Barbara Russo, Andrea Janes, Vincenzo Ferme, André van Hoorn, Henning Schulz, Cabral Lima:
Improving Predictability of User-Affecting Metrics to Support Anomaly Detection in Cloud Services. IEEE Access 8: 198152-198167 (2020)

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