Abstract

The utilization of AI/ML techniques in transport networks is a current area of focus of the research community and industry alike. Leveraging the availability of data to improve how networks are operated holds the promise of simplified network operation and enhanced network optimization. However, materializing the promise of AI/ML will demand a joint effort and close cooperation between system vendors and network operators as it can only be achieved through a shift in long standing operational paradigms. That change is already well under way in the transition from Central Office centric networks towards Datacenter networking. This paper discusses the adoption of AI/ML in production networks as part of this ongoing transformation.

© 2020 The Author(s)