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Work item:
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Y.CFL-FW-AN
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Subject/title:
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Cloud based Federated Learning Framework for Autonomous Networks
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Status:
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Under study
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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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Q4-2027 (Medium priority)
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Liaison:
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-
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Supporting members:
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SPbSUT, Russian Federation, RCC
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Summary:
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This Recommendation describes an architectural framework that combines federated learning (FL) and cloud computing. This architectural framework is specifically designed to enhance the capabilities of Autonomous Networks by significantly reducing the network load and improving the efficiency of distributed learning. It also combines the capabilities of FL and cloud computing, which allows for a reduction in communication volume which is crucial for scalable and responsive autonomous operations – while simultaneously preserving the quality and robustness of model training across the network segments.
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Comment:
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-
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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:
2025-11-14 16:43:04
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Last update:
2025-11-14 16:59:50
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