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Work item:
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Y.3183 (ex Y.ML-IMT2020-VNS)
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Subject/title:
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Framework for network slicing management assisted by machine learning leveraging QoE feedback from verticals
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Status:
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Approved on 2023-01-13 [Issued from previous study period]
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Approval process:
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AAP
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Type of work item:
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Recommendation
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Version:
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New
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Equivalent number:
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-
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Timing:
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-
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Liaison:
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ITU-T SG9, ITU-T SG16, ETSI ENI, ETSI ZSM
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Supporting members:
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Orange, IBM, Altice (MEO Serviços de Comunicações)
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Summary:
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This Recommendation provides a framework for machine learning assisted network slicing management, leveraging vertical end users’ feedback on QoE, which can help achieve run-time optimisation of user perceived performance. The overall architecture, components, workflow and related APIs of this framework are specified with respect to the high-level requirements identified. A use case is provided in appendix to show an application example of this framework. Example implementations of the key APIs are also provided.
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Comment:
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Based on the FG-ML5G Deliverables
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Reference(s):
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Historic references:
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Contact(s):
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| ITU-T A.5 justification(s): |
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First registration in the WP:
2020-08-04 17:28:41
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Last update:
2022-11-28 15:15:55
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