Autonomous and Real-Time Network Diagnosis with Machine Learning

Abstract

We present an autonomous real-time network diagnosing platform toward network operation automation. The platform consists of four functions: network monitoring, analyzing, deduction, and modeling. We discussed two PoC demonstrations, including a novel optical fiber bending detection using digital coherent detection with machine learning and autonomous network protection that utilizes fiber-bending information.