Committed to connecting the world

  •  
wtisd

ITU-T Recommendations

Search by number:
Others:
Skip Navigation Links
Content search
Advanced search
Provisional name
Equivalent number
Formal description
Study Groups tree viewExpand Study Groups tree view

ITU-T Y.3182 (09/2022)

عربي | 中文 | English | Español | Français | Русский
Machine learning based end-to-end multi-domain network slice management and orchestration
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.
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
Status: In force
Maintenance responsibility: ITU-T Study Group 13
Further details: Patent statement(s)
Development history
[21 related work items in progress]