IDNET -- The IDNet (Intelligence-Defined Network)


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The IDNet (Intelligence-Defined Network) is aiming to applying Artificial Intelligence technologies, including Machine Learning mechanisms, to networks. It can intelligently learn the network environment and react to dynamic situations. It can learn and complete complicated tasks, such as traffic load balancing associated with link utilities, autonomic network operation & maintenance dynamic flow&path controlling in large-scale network, etc. It can even predict the future network situation for proactive controlling. There will be new requirements for networks towards IDN, and new work on standards.

This mail list is for discussion of IDN architecture, which focuses on applying machine learning into network, gap analysis, potential standard opportunities, etc. Its topics are including, but not limited:

- use cases that AI could better manage&control network over traditional
- architecture or reference model for the Intelligence-Defined Network
- integrate IDN with various network infrastructure architectures and IETF
- gap analysis from the current and emerging IETF standards towards IDN
- data requirements for AI network controlling, including new
measurement technologies
- network data selection, data structure & protocol for data transmission
- distribution, and modifications and extensions if needed, for AI
controlling result to network elements
- integrate network expert knowledge and AI controlling mechanisms

The scope of this mail list discussion is limited to machine learning. Identified standard work on IETF protocols will be provided to the appropriate Working Group, e.g. for network control-protocol functions, TEAS (e.g. ACTN) and PCE.

To see the collection of prior postings to the list, visit the IDNET Archives.

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