The reinforcement learning-based routing, modulation, and spectrum assignment has been
regarded as an emerging paradigm for resource allocation in the elastic optical networks …

In this letter, we study the deep reinforcement learning (DRL)-based routing, modulation and
spectrum assignment problem in the elastic optical networks. We emphasize the importance …

This paper proposes DeepRMSA, a deep reinforcement learning framework for routing,
modulation and spectrum assignment (RMSA) in elastic optical networks (EONs) …

We design an effective and scalable Deep Reinforcement Learning (DRL) approach for the
Routing, Modulation and Spectrum Assignment (RMSA) problem in elastic optical networks …

Deep reinforcement learning (DRL) has been applied to the routing, modulation, and
spectrum assignment (RMSA) in elastic optical networks (EON), enabling the learning of …

Research on the routing and spectrum assignment (RSA) problem has long been conducted
with the aim of efficiently utilizing the frequency resources of optical networks. Given the …

We propose Mask RSA, an end-to-end deep reinforcement learning-based routing and
spectrum assignment for elastic optical networks. Mask RSA masks unassignable choices …

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 …

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 …

The study of online routing and spectrum allocation (RSA) problem has assumed increasing
importance due to the exponential growth of dynamic traffic with uncertainty in elastic optical …