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Work item:
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L.AIA_RS
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Subject/title:
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Framework of AI agents in resource scheduling for environmentally efficient data center infrastructure
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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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2027-12 (Medium priority)
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Liaison:
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ITU-T SG13, ITU-T SG21, ISO/IEC JTC1/SC39, ISO/IEC JTC1/SC42
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Supporting members:
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State Grid Corporation of China; China Information Communication Technologies Group; Wuhan University; Huazhong University of Science & Technology; China University of Geosciences (Wuhan)
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Summary:
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This Recommendation proposes the framework and strategies of AI agents in resource scheduling for environmentally efficient data center infrastructure. By uniformly modelling and real-time sensing the heterogeneous resources such as computing, storage, network, and power supply, it achieves intelligent collaborative scheduling of the distributed multi-agent system. The framework adopts two-layer AI agents to support dynamic resource allocation, cross-domain collaborative optimization, and energy efficiency priority scheduling. Under the premise of meeting the quality of service (QoS), it improves resource utilization, reduces energy consumption, and effectively supports the evolution of data center infrastructure towards sustainability and intelligence.
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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:
2026-07-01 10:03:47
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Last update:
2026-07-01 10:11:28
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