Elastic optical networks (EONs) operating in the C-band have been widely deployed
worldwide. However, two major technologies—multiband elastic optical networks (MB …

The constantly increasing traffic volume triggers the fast development of new optimization
methods for backbone optical networks. Operators seek new ways to improve several …

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

The knowledge about future traffic volumes is beneficial for the network operators in many
areas. Short-term forecasting of multiple traffic types helps with efficient resource utilization …

This work focuses on finding efficient Machine Learning (ML) method for traffic prediction in
optical network. Considering optical networks' characteristics, we predict fixed bitrate levels …

Relentless competition among communications ser-vice providers, increasing expectations
of users, and escalating variety of new applications and services trigger the need to develop …

The constantly increasing internet traffic and rising network requirements trigger fast
development and implementation of new networking architectures and technologies …

The overall network volume in backbone optical networks is constantly growing, composed
of many smaller network services with increasing trends and various seasonality. Due to the …

The constant increase in traffic volume triggers the development of new network optimization
methods. Machine learning techniques are one of the promising research directions, as they …

Knowledge about future traffic in backbone optical networks may greatly improve a range of
tasks that Communications Service Providers (CSPs) have to face. This work proposes a …