AI-Driven Framework for Scalable Management of Network Slices

Luis Blanco,Slawomir Kuklinski,Engin Zeydan,Farhad Rezazadeh, Ashima Chawla, Lanfranco Zanzi, Francesco Devoti,Robert Kolakowski, Vasiliki Vlahodimitropoulou,Ioannis Chochliouros, Anne-Marie Bosneag, Sihem Cherrared,Luis A. Garrido,Sergio Barrachina-Munoz,Josep Mangues

IEEE COMMUNICATIONS MAGAZINE(2023)

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摘要
This article describes a scalable solution for orchestrating and managing a massive number of network slices that leverages Artificial Intelligence (AI) techniques to design robust and sustainable networks. To achieve this goal, the proposed approach decomposes the management and orchestration (M&O) plane using separation of concerns and uses AI techniques to automate M&O operations. The M&O automation is achieved through the use of multiple, distributed and AI-driven control loops. The control loops have different goals and may work on the node level, slice level, inter-slice level or orchestration domain level. We also present a case study of using the proposed distributed intelligent components to scale, optimize and improve the network infrastructure. Finally, we briefly describe some challenges and future directions for scalable M&O on the road to 6G.
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关键词
6G mobile communication,Renewable energy sources,Runtime,Automation,Roads,Buildings,Information processing,Network slicing,Artificial intelligence,Scalability
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