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Network Slicing Meets Artificial Intelligence: an AI-based Framework for Slice Management

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commag19_slicing-ai_postprint.pdf (503.3Kb)
Identificadores
URI: http://hdl.handle.net/20.500.12761/843
DOI: 10.1109/MCOM.001.1900653
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Autor(es)
Bega, Dario; Gramaglia, Marco; Garcia-Saavedra, Andres; Fiore, Marco; Banchs, Albert; Costa-Perez, Xavier
Fecha
2020-06
Resumen
Network slicing is an emerging paradigm in mobile networks that leverages Network Function Virtualization (NFV) to enable the instantiation of multiple virtual networks –named slices– over the same physical network infrastructure. The operator can allocate to each slice dedicated resources and customized functions that allow meeting the highly heterogeneous and stringent requirements of modern mobile services. Managing functions and resources under network slicing is a challenging task that requires making efficient decisions at all network levels, in some cases even in real-time, which can be achieved by integrating artificial intelligence (AI) in the network. We outline a general framework for AI-based network slice management, introducing AI in the different phases of the slice lifecycle, from admission control to dynamic resource allocation in the network core and at the radio access. A sensible use of AI for network slicing results in strong benefits for the operator, with expected performance gains between 25% and 80% in representative case studies.
Compartir
Ficheros
commag19_slicing-ai_postprint.pdf (503.3Kb)
Identificadores
URI: http://hdl.handle.net/20.500.12761/843
DOI: 10.1109/MCOM.001.1900653
Metadatos
Mostrar el registro completo del ítem

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