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Microservice-Based Unsupervised Anomaly Detection Loop for Optical Networks

Authors: Natalino, Carlos; Manso, Carlos; Gifre, Lluis; Muñoz, Raul; Vilalta, Ricard; Furdek, Marija; Monti, Paolo;

Microservice-Based Unsupervised Anomaly Detection Loop for Optical Networks

Abstract

Unsupervised learning (UL) is a technique to detect previously unseen anomalies without needing labeled datasets. We propose the integration of a scalable UL-based inference component in the monitoring loop of an SDN-controlled optical network.

Country
Sweden
Keywords

Bioinformatics (Computational Biology), Fiber optic networks, Labeled dataset, Computer Science, Computer Engineering, Anomaly detection, Unsupervised anomaly detection

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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OpenAIRE UsageCountsViews provided by UsageCounts
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3
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14
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