SElf-mAnaged Sustainable high-capacity Optical Networks

Información del proyecto

SEASON

Identificador del acuerdo de subvención: 101096120

DOI

10.3030/101096120

Proyecto cerrado

Fecha de la firma de la CE 21 Noviembre 2022

Fecha de inicio 1 Enero 2023

Fecha de finalización 31 Diciembre 2025

Financiado con arreglo a

• Digital, Industry and Space

Coste total

€ 6 363 485,50

Aportación de la UE

€ 5 955 098,00

Coordinado por

CONSORZIO NAZIONALE INTERUNIVERSITARIO PER LE TELECOMUNICAZIONI
Italy

Periodic Reporting for period 1 - SEASON (SElf-mAnaged Sustainable high-capacity Optical Networks)

Período documentado: 2023-01-01 hasta 2024-06-30

Resumen del contexto y de los objetivos generales del proyecto

SEASON project started on Jan 2023. The goal of the SEASON project is to design and validate a transport network infrastructure able to support beyond 5G and new emerging services, relying on the joint usage of Multi-Band (ΜΒ) and SDM, spanning the access, aggregation, and metro/long-haul segments, supporting the requirements for x-haul, further integrating the packet/optical and computing layers, and targeting efficient networks in terms of capacity and energy efficiency.

The targeted architecture considers joint MB and SDM (MBoSDM) and SDM-Passive Optical Networks (PON) networking, in terms of transmission and switching, while addressing innovation in terms of sliceable Bandwidth Variable Transceivers (S-BVTs) enabling Point-to-MultiPoint (P2MP. Along with the integration of (coherent) pluggable optical modules, smart Network Interface Cards (NICs) or the latest generation Data Processing Units (DPU) on open packet/optical white boxes, it will allow decoupling and providing open control and network management. Thus, such complex infrastructure requires rethinking the control and orchestration systems towards autonomous optical networks, adopting more agile DevOps methodologies. SEASON will leverage on cognitive networks powered by streaming telemetry, real-time network measurements and Artificial Intelligence/ Machine Learning (AI/ML)-aided service management for near-real time network operation, moving intelligence as close as possible to the data plane.

Trabajo realizado desde el comienzo del proyecto hasta el final del período abarcado por el informe y los principales resultados hasta la fecha

During the first period of the project, effort was devoted to defining network requirements and Use Cases. In particular, use case requirements have been mapped to network requirements and KPIs and the main drivers and challenges were identified. This has allowed SEASON to define a network architecture that can scale up network capacity to cope with advanced user requirement and new emerging services. In addition, work was also devoted in defining data and control plane requirements to support SEASON architectural design. This mandates the use of ultra-wideband communication and brings coherent transceiver close to the access segment.

During the 1st period of the project modeling of the main data plane technologies was carried out namely for flexigrid, Multi-band and SDM as the most promising technology options to cost-efficiently scale network capacity and meet the increasing traffic demand. In addition, the first approach of the control plane was portrayed. This relies on NetDevOps approaches jointly with AI/ML in support of network operation and network orchestration, including Multi-Agent Systems (MAS). On top of this approach, AI/ML algorithms are applied for the near-real time control of network resources and services aiming at reducing energy consumption and ensuring perfosrmance, including moving intelligence as close as possible to the data plane, and devising a MAS distributed system,

Avances que van más allá del estado de la técnica e impacto potencial esperado (incluida la repercusión socioeconómica y las implicaciones sociales más amplias del proyecto hasta la fecha)

During the 1st period of the project, the SEASON architectural solution has been defined. One of its prime objectives was to translate user case requirements to network requirements and then perform data plane modelling to achieve these. (Obj.1). The 5G evolution and beyond has pushed innovations in the optical x-haul and metro networks as isolated systems. B5G requires a comprehensive integrated solution across all segments, targeting a sustainable capacity scaling. SEASON proposed architecture makes use of MBoSDM technology as a sustainable means to increase network capacity. It foresees an x120 capacity increase as compared to current C-band solutions. Further SEASON reference architecture exploits coherent intelligent pluggable transceivers, employed at the edge. This will enable a pay-as-you-grow approach, which intrinsically provides larger flexibility and scalability for B5G emerging services.

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