The new standard, ITU-T Y.3172 , of the ITU-T Focus Group "Machine Learning for Future Networks including 5G" (FG-ML5G ) establishes a basis for the cost-effective integration of Machine Learning (ML) into 5G and future networks. The ITU-T Y.3172 architectural framework is the first of a nascent series of ITU standards addressing Machine Learning’s contribution to networking. ITU Y.3172 is part of the focus group ITU-T Study Group 13 .
"Machine Learning will change the way we operate and optimize networks," says Slawomir Stanczak, Chairman of the ITU-T Focus Group FG-ML5G and Head of Wireless Communications and Networks Department at Fraunhofer HHI. "Every company in the networking business is investigating the introduction of Machine Learning, with a view to optimizing network operations, increasing energy efficiency and curtailing the costs of operating a network," says Stanczak. "This ITU-T Y.3172 architectural framework provides a common point of reference to improve industry’s orientation when it comes to the introduction of Machine Learning into mobile networks."
Machine Learning holds great promise to enhance network management and orchestration. Drawing insight from network-generated data, Machine Learning can yield predictions to support the optimization of network operations and maintenance. This optimization is becoming increasingly challenging, and increasingly important, as networks gain in complexity to support the coexistence of a diverse range of information and communication technology (ICT) services.
Network operators aim to fuel Machine Learning models with data correlated from multiple technologies and levels of the network. They are calling for deployment mechanisms able to ‘future-proof’ their investments in Machine Learning. And they are in need of interfaces to transfer data and trained ML models across ML functionalities at multiple levels of the network. The ITU-T Y.3172 architectural framework is designed to meet these requirements and it is the first of a nascent series of ITU standards addressing Machine Learning’s contribution to networking. "A range of ITU standards under development will complement and complete the architectural framework described by ITU Y.3172," says Ram. "Collectively these standards will provide a full toolkit to build Machine Learning into our networks."
The complete article can be found here .