Digital twin (DT) has revolutionized optical communication networks by enabling their full life-
cycle management, including planning, prediction, optimization, upgrade, and …

We consider the problem of classifying hardware failures in microwave networks given a
collection of alarms using Machine Learning (ML). While ML models have been shown to …

In optical networks, reliable failure detection is essential for maintaining quality of service.
The methodology has evolved from traditional performance threshold-driven approaches to …

Optical in-phase and quadrature (IQ) constellations enclose valuable information regarding
the optical elements traversed by the optical signal. Such information can be extracted and …

Reconfigurable optical add/drop multiplexer (ROADM) nodes are evolving towards high-
degree architectures to support growing traffic and enable flexible network connectivity. Due …

Reliable fault diagnosis is crucial for ensuring the stable operation of optical networks.
Recently, data-driven techniques have demonstrated significant advantages in fault …

The uneven occurrence of certain types of failures in optical networks results in a scarcity of
data for less frequent failures, leading to imbalanced datasets for training machine learning …

The health state of optical modules is crucial for ensuring the stable and reliable operation of
optical transport networks (OTNs). Recently, data-driven techniques have shown immense …

Failure management in optical networks usually deals with the processing of alarms,
including alarm classification. The alarms data obtained from network management systems …

We propose an expertise-embedded approach for failure management of optical modules in
OTN that incorporates expert decision-making logic into data-driven ML models, thereby …