Programmable Multilayer INT: An Enabler for AI-Assisted Network Automation

Recently, the fast development of backbone networks has made the traffic, services, and infrastructure of packet-over-optical networks increasingly complicated. This stimulates research and development on fine-grained and real-time performance monitoring and troubleshooting. In this article, we propose a ProML-INT system to oversee packet-over-optical networks in real time and enable customized performance monitoring and troubleshooting. We introduce the system design in detail, and explain how to control the overhead of multilayer INT ML-INT by inserting INT fields in packets selectively. Experiments demonstrate the ProML-INT system, a small-scale packet-over-optical network testbed. The experimental results confirm that our proposal can monitor packet and optical layers jointly in real time, and the homemade data analyzer in it can leverage artificial intelligence to identify the root causes of exceptions in packet-over-optical networks correctly and promptly.