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A Flexible and Scal...
A Flexible and Scalable ML-Based Diagnosis Module for Optical Networks: A Security Use Case
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- Natalino Da Silva, Carlos, 1987 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Gifre, Lluis (författare)
- Centre Tecnològic de Telecomunicacions de Catalunya (CTTC),Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
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- Moreno-Muro, Francisco-Javier (författare)
- Atos Spain
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- Gonzalez-Diaz, Sergio (författare)
- Atos Spain
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- Vilalta, Ricard (författare)
- Centre Tecnològic de Telecomunicacions de Catalunya (CTTC),Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
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- Munoz, Raul (författare)
- Centre Tecnològic de Telecomunicacions de Catalunya (CTTC),Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
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- Monti, Paolo, 1973 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Furdek Prekratic, Marija, 1985 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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(creator_code:org_t)
- 2023
- 2023
- Engelska.
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Ingår i: Journal of Optical Communications and Networking. - 1943-0620 .- 1943-0639. ; 15:8, s. C155-C165
- Relaterad länk:
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https://research.cha... (primary) (free)
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https://research.cha...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- To support the pervasive digital evolution, optical network infrastructures must be able to quickly and effectively adapt to the changes arising from traffic dynamicity or external factors such as faults and attacks. Network automation is crucial for enabling dynamic, scalable, resource-efficient, and trustworthy network operations. Novel telemetry solutions enable optical network management systems to obtain fine-grained monitoring data from devices and channels as the first step towards the near-real-time diagnosis of anomalies such as security threats and soft failures. However, the collection of large amounts of data creates a scalability challenge related to processing the data within the desired monitoring cycle regardless of the number of optical services being analyzed. This paper proposes a module that leverages the cloud native software deployment approach to achieve near-real-time \ac{ML}-assisted diagnosis of optical channels. The results obtained over an emulated physical-layer security scenario demonstrate that the architecture successfully scales the necessary components according to the computational load, and consistently achieves the desired monitoring cycle duration over a varying number of monitored optical channels.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Engineering (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Telekommunikation (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Telecommunications (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
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- ref (ämneskategori)
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