| Machine learning based end-to-end multi-domain network slice management and orchestration |
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Recommendation ITU-T Y.3182 describes an intelligent cost-effective network management and orchestration framework that can cope with the challenges of multi-domain network slicing, while minimizing human intervention towards full automation of slice lifecycle management and runtime operation.
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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| Citation: |
https://handle.itu.int/11.1002/1000/15059 |
| Series title: |
Y series: Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
Y.3000-Y.3499: Future networks |
| Approval date: |
2022-09-29 |
| Provisional name: | Y.ML-IMT2020-E2E-MGMT |
| Approval process: | AAP |
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Status: |
In force |
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Maintenance responsibility: |
ITU-T Study Group 13 |
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Further details: |
Patent statement(s)
Development history
[18 related work items in progress]
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| Ed. |
ITU-T Recommendation |
Status |
Summary |
Table of Contents |
Download |
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1
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Y.3182 (09/2022)
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In force
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here
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here
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here
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| Title |
Approved on |
Download |
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ITU-T Focus Group IMT-2020 Deliverables
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2017
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here
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Multiple radio access technologies
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2012
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here
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Future networks
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2012
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here
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