Failure management plays a significant role in optical networks. It ensures secure operation,
mitigates potential risks, and executes proactive protection. Machine learning (ML) is …

Optical access networks are envisioned to become increasingly complex as they support
more and more diverse and immersive services, each with a different capacity, latency, and …

Artificial intelligence (AI) and machine learning (ML) continue to demonstrate substantial
capabilities in solving a wide range of optical-network-related tasks such as fault …

Fault location is an essential part of optical network operation and maintenance, and
network operators have expectations to achieve highly accurate and precise fault location …

Artificial Intelligence (AI) has demonstrated superhuman capabilities in solving a significant
number of tasks, leading to widespread industrial adoption. For in-field network …

Traffic prediction is an evergreen research topic in networking, with modern allocation
algorithms often utilizing forecasts for optimized decisions. However, the employed machine …

The recent technological advances create increased network capacity demand, highlighting
the need for new network optimization methods. However, the proposed solutions require …

This paper considers the problem of predicting whether or not a transmitter and a receiver
are in Line-of-Sight (LOS) condition. While this problem can be easily solved using a digital …

The rapid development of telecommunication networks brings new optimization problems
and the urgent need for dedicated and highly efficient solution methods. Recently, the idea …

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