This paper evaluates different aspects of the performance of a solution for routing and
spectrum allocation in elastic optical networks. The evaluation includes the experimentation …

We present a solution based on deep reinforcement learning (DRL) that jointly addresses
spectrum allocation and latency constraint in EONs. The results show that using a simple …

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 …

Reinforcement learning techniques have been successfully applied to the routing and
spectrum assignment problem in elastic optical networks. These techniques offer a …

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 …

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 …

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 …

Global Internet traffic will continue to grow at high speed in the forthcoming years. To be able
to meet this continuous and rapid growth, network operators are moving towards a new …

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 …