Journal
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
Volume 18, Issue 3, Pages 2627-2640Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNSM.2021.3077543
Keywords
Signal to noise ratio; Degradation; Location awareness; Object recognition; Analytical models; Optical filters; Optical fiber networks; Soft-Failure Identification and Localization; Network Automation
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Funding
- AEI/FEDER through the TWINS project [TEC2017-90097-R]
- ICREA institution
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This study proposes a method of comparing QoT in optical devices to predict device failures by estimating the differences between estimated and measured values, achieving accurate detection and localization, and effectively identifying issues before degradation occurs.
The performance of optical devices can degrade because of aging and external causes like, for example, temperature variations. Such degradation might start with a low impact on the Quality of Transmission (QoT) of the supported lightpaths (soft-failure). However, it can degenerate into a hard-failure if the device itself is not repaired or replaced, or if an external cause responsible for the degradation is not properly addressed. In this work, we propose comparing the QoT measured in the transponders with the one estimated using a QoT tool. Those deviations can be explained by changes in the value of input parameters of the QoT model representing the optical devices, like noise figure in optical amplifiers and reduced Optical Signal to Noise Ratio in the Wavelength Selective Switches. 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.
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