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DAEMON

Financiado

Cerrado

Network intelligence for aDAptive and sElf Learning MObile Networks

The success of Beyond 5G (B5G) systems will largely depend on the quality of the Network Intelligence (NI) that will fully automate network management. Artificial Intelligence (AI) models are commonly regarded as the cornerstone f... ver más

31/03/2024

IMDEA NETWORKS

5M€

Presupuesto del proyecto: 5M€

Líder del proyecto

FUNDACION IMDEA NETWORKS No se ha especificado una descripción o un objeto social para esta compañía.

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Ver 13 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2024-03-31

ICT-52-2020: 5G PPP – Smart Connectivity beyond... Specific Challenge:The challenge is to go well beyond the 5G capabilities developed under 3G PPP rel...

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Información adicional privada

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13 Participantes

IMDEA NETWORKS

694.38K€ | Lider

NOKIA BELL

575.00K€ | Participante

ZETTASCALE TECHNOLOGY SARL

364.50K€ | Participante

SRS

372.50K€ | Participante

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Duración del proyecto: 39 meses Fecha Inicio: 2020-12-08
Fecha Fin: 2024-03-31

Líder del proyecto

FUNDACION IMDEA NETWORKS No se ha especificado una descripción o un objeto social para esta compañía.

Presupuesto del proyecto 5M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto The success of Beyond 5G (B5G) systems will largely depend on the quality of the Network Intelligence (NI) that will fully automate network management. Artificial Intelligence (AI) models are commonly regarded as the cornerstone for NI design; indeed, AI models have proven extremely successful at solving hard problems that require inferring complex relationships from entangled and massive (e.g., traffic) data. However, AI is not the best solution for every NI task; and, when it is, the dominating trend of plugging ‘vanilla’ AI into network controllers and orchestrators is not a sensible choice. Departing from the current hype around AI, DAEMON will set forth a pragmatic approach to NI design. The project will carry out a systematic analysis of which NI tasks are appropriately solved with AI models, providing a solid set of guidelines for the use of machine learning in network functions. For those problems where AI is a suitable tool, DAEMON will design tailored AI models that respond to the specific needs of network functions, taking advantage of the most recent advances in machine learning. Building on these models, DAEMON will design an end-to-end NI-native architecture for B5G that fully coordinates NI-assisted functionalities. The advances to NI devised by DAEMON will be applied in practical network settings to: (i) deliver extremely high performance while making an efficient use of the underlying radio and computational resources; (ii) reduce the energy footprint of mobile networks; and (iii) provide extremely high reliability beyond that of 5G systems. To achieve this, DAEMON will design practical algorithms for eight concrete NI-assisted functionalities, carefully selected to achieve the objectives above. The performance of the DAEMON algorithms will be evaluated in real-world conditions via four experimental sites, and at scale with data-driven approaches based on two nationwide traffic measurement datasets, against nine ambitious yet feasible KPI targets.

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