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Work item:
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Y.3182 (ex Y.ML-IMT2020-E2E-MGMT)
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Subject/title:
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Machine learning based end-to-end multi-domain network slice management and orchestration
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Status:
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Approved on 2022-09-29 [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 the framework and requirements of machine learning based end-to-end network slice management and orchestration in multi-domain environments. It addresses the following subjects:
Overview and interoperability requirements of machine learning based multi-domain end-to-end network slice management and orchestration;
Functional requirements of machine learning based multi-domain end-to-end network slice management and orchestration;
Framework of machine learning based multi-domain end-to-end network slice management and orchestration;
Cognitive components for the framework.
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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 16:48:56
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Last update:
2022-07-27 09:31:35
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