Survey on machine learning for traffic-driven service provisioning in optical networks

T Panayiotou, M Michalopoulou… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The unprecedented growth of the global Internet traffic, coupled with the large spatio-
temporal fluctuations that create, to some extent, predictable tidal traffic conditions, are …

Hierarchical reinforcement learning in multi-domain elastic optical networks to realize joint RMSA

L Xu, YC Huang, Y Xue, X Hu - Journal of Lightwave …, 2023 - ieeexplore.ieee.org
To improve the network scalability, a large elastic optical network is typically segmented into
multiple autonomous domains, where each domain possesses high autonomy and privacy …

Nonlinear Impairment-Aware RMSA Under the Sliding Scheduled Traffic Model for EONs Based on Deep Reinforcement Learning

Y Zou, X Cai, M Zhu, J Gu, Y Wang… - Journal of Lightwave …, 2023 - ieeexplore.ieee.org
The elastic optical network (EON) can accommodate dynamic and diverse demands of next-
generation applications by provisioning flexible lightpaths for them. Consequently, blocking …

Deep-reinforcement-learning-based RMSCA for space division multiplexing networks with multi-core fibers [Invited Tutorial]

Y Teng, C Natalino, H Li, R Yang, J Majeed… - Journal of Optical …, 2024 - opg.optica.org
The escalating demands for network capacities catalyze the adoption of space division
multiplexing (SDM) technologies. With continuous advances in multi-core fiber (MCF) …

PtrNet-RSA: A Pointer Network-based QoT-aware Routing and Spectrum Assignment Scheme in Elastic Optical Networks

Y Cheng, S Ding, Y Shao… - Journal of Lightwave …, 2024 - ieeexplore.ieee.org
To enable flexible service provisioning in elastic optical networks (EONs), quality of
transmission (QoT) estimation and dynamic routing and spectrum assignment (RSA) are …

Fast-Convergence Reinforcement Learning for Routing in LEO Satellite Networks

Z Ding, H Liu, F Tian, Z Yang, N Wang - Sensors, 2023 - mdpi.com
Fast convergence routing is a critical issue for Low Earth Orbit (LEO) constellation networks
because these networks have dynamic topology changes, and transmission requirements …

Experimental evaluation of a latency-aware routing and spectrum assignment mechanism based on deep reinforcement learning

C Hernández-Chulde, R Casellas… - Journal of Optical …, 2023 - opg.optica.org
The introduction of futuristic and challenging use cases of 5G and 6G communications will
demand strict requirements in terms of high bandwidth and low latency. Optical backbone …

Intelligent performance inference: A graph neural network approach to modeling maximum achievable throughput in optical networks

R Matzner, R Luo, G Zervas, P Bayvel - APL Machine Learning, 2023 - pubs.aip.org
One of the key performance metrics for optical networks is the maximum achievable
throughput for a given network. Determining it, however, is a nondeterministic polynomial …

Reinforcement learning applied to the routing and spectrum assignment in elastic optical networks

S Arce, LA Albertini, I Ríos… - 2022 IEEE Latin …, 2022 - ieeexplore.ieee.org
Elastic Optical Networks (EON) has emerged as technology in optical networks whose
architecture can respond to the growing need for elasticity in allocating optical network …

Entropy-based Reward Design for Deep Reinforcement Learning-enabled Routing, Modulation and Spectrum Assignment of Elastic Optical Networks

Y Tu, B Tang, YC Huang - 2022 Asia Communications and …, 2022 - ieeexplore.ieee.org
We present a new reward design for the deep reinforcement learning (DRL)-based routing,
modulation and spectrum assignment in the elastic optical networks (EONs). The …