Using a SNR Digital Twin for Failure Management

The development of Digital Twins to represent the optical transport network might enable multiple applications for network operation, including automation and fault management. In this work, we use GNPy as a Signal to Noise Ratio (SNR) digital twin of the optical network for failure management applications. The methodology proposed for failure management consists in comparing the QoT measured in the transponders with the one estimated using the digital twin and try to explain detected deviations as changes in the value of input parameters of the Quality of Transmission (QoT) model representing the optical devices, like noise figure (NF) in optical amplifiers (OA) and reduced Optical SNR in the Wavelength Selective Switches (WSS). By applying reverse engineering, the value of those modeling parameters can be estimated as a function of the observed QoT of the lightpaths. Experiments reveal high accuracy estimation of modeling parameters, and results obtained by simulation show large anticipation of soft-failure detection and localization, as well as accurate identification of degradations before they have a major impact on the network.