| 1. |
- Adanza, Daniel, et al.
(author)
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IntentLLM: An AI Chatbot to Create, Find, and Explain Slice Intents in TeraFlowSDN
- 2024
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In: 2024 IEEE 10th International Conference on Network Softwarization, NetSoft 2024. ; , s. 307-309
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Conference paper (peer-reviewed)abstract
- A large language model (LLM) chatbot is integrated within TeraFlowSDN for intent manipulation. The resulting chatbot is capable of understanding the context and is able to carry out three actions: create, find, and explain intents using natural language while being flexible regarding the language used.
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| 2. |
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| 3. |
- Fallgren, Mikael, et al.
(author)
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Fifth-Generation Technologies for the Connected Car Capable Systems for Vehicle-to-Anything Communications
- 2018
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In: IEEE Vehicular Technology Magazine. - 1556-6080 .- 1556-6072. ; 13:3, s. 28-38
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Journal article (peer-reviewed)abstract
- Two strong technology trends, one in the mobile communications industry and the other in the automotive industry, are becoming interwoven and will jointly provide new capabilities and functionality for upcoming intelligent transport systems (ITSs) and future driving. The automotive industry is on a path where vehicles are continuously becoming more aware of their environment due to the addition of various types of integrated sensors. At the same time, the amount of automation in vehicles increases, which, with some intermediate steps, will eventually culminate in fully automated driving without human intervention. Along this path, the amount of interactions rises, both in-between vehicles and between vehicles and other road users, and with an increasingly intelligent road infrastructure. As a consequence, the significance and reliance on capable communication systems for vehicleto-anything (V2X) communication is becoming a key asset that will enhance the performance of automated driving and increase further road traffic safety with combination of sensor-based technologies [1].
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| 4. |
- Famelis, Panagiotis, et al.
(author)
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P5: Event-driven Policy Framework for P4-based Traffic Engineering
- 2023
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In: Proceedings of the 24th International Conference on High Performance Switching and Routing. - 9781665476409 ; 2023-June
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Conference paper (peer-reviewed)abstract
- We present P5, an event-driven policy framework that allows network operators to realize end-to-end policies on top of P4-based data planes in an intuitive and effective manner. We demonstrate how P5 adheres to a service-level agreement (SLA) by applying P4-based traffic engineering with latency constraints.
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| 5. |
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| 6. |
- Natalino Da Silva, Carlos, 1987, et al.
(author)
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A Flexible and Scalable ML-Based Diagnosis Module for Optical Networks: A Security Use Case
- 2023
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In: Journal of Optical Communications and Networking. - 1943-0620 .- 1943-0639. ; 15:8, s. C155-C165
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Journal article (peer-reviewed)abstract
- 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.
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| 7. |
- Natalino Da Silva, Carlos, 1987, et al.
(author)
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Microservice-Based Unsupervised Anomaly Detection Loop for Optical Networks
- 2022
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In: 2022 Optical Fiber Communications Conference and Exhibition, OFC 2022 - Proceedings.
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Conference paper (peer-reviewed)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.
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| 8. |
- Natalino Da Silva, Carlos, 1987, et al.
(author)
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Microservice-Based Unsupervised Anomaly Detection Loop for Optical Networks
- 2016
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In: Optics InfoBase Conference Papers. ; 2016
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Conference paper (peer-reviewed)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.
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| 9. |
- Natalino Da Silva, Carlos, 1987, et al.
(author)
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Scalable and Efficient Pipeline for ML-based Optical Network Monitoring
- 2023
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In: 2023 Optical Fiber Communications Conference and Exhibition, OFC 2023 - Proceedings.
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Conference paper (peer-reviewed)abstract
- We demonstrate a scalable processing of OPM data using ML to detect anomalies in optical services at run time. A dashboard will show operational SDN controller metrics, raw OPM data, and the ML assessment results.
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| 10. |
- Natalino Da Silva, Carlos, 1987, et al.
(author)
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Scalable Physical Layer Security Components for Microservice-Based Optical SDN Controllers
- 2021
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In: European Conference on Optical Communication, ECOC. ; 2021
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Conference paper (peer-reviewed)abstract
- We propose and demonstrate a set of microservice-based security components able to perform physical layer security assessment and mitigation in optical networks. Results illustrate the scalability of the attack detection mechanism and the agility in mitigating attacks.
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| 11. |
- Vilalta, Ricard, et al.
(author)
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TeraFlow: Secured autonomic traffic management for a tera of SDN flows
- 2021
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In: 2021 Joint European Conference on Networks and Communications and 6G Summit, EuCNC/6G Summit 2021. - 9781665415262 ; , s. 377-382
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Conference paper (peer-reviewed)abstract
- TeraFlow proposes a new type of secure, cloud-native Software Defined Networking (SDN) controller that will radically advance the state-of-the-art in beyond 5G networks by introducing novel micro-services architecture, and provide revolutionary features for both flow management (service layer) and optical/microwave network equipment integration (infras-tructure layer) by adapting new data models. TeraFlow will also incorporate security using Machine Learning (ML) and forensic evidence for multi-tenancy based on Distributed Ledgers. Finally, this new SDN controller shall be able to integrate with the current Network Function Virtualization (NFV) and Multi-access Edge Computing (MEC) frameworks as well as to other networks. The target pool of TeraFlow stakeholders expands beyond the traditional telecom operators towards edge and hyperscale cloud providers.
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