Building a Graph-based Deep Learning network model from captured traffic traces

no code implementations • 18 Oct 2023 • Carlos Güemes-Palau, Miquel Ferriol Galmés, Albert Cabellos-Aparicio, Pere Barlet-Ros

In this paper we propose a Graph Neural Network (GNN)-based solution specifically designed to better capture the complexities of real network scenarios.

Accelerating Deep Reinforcement Learning for Digital Twin Network Optimization with Evolutionary Strategies

1 code implementation • 1 Feb 2022 • Carlos Güemes-Palau, Paul Almasan, Shihan Xiao, Xiangle Cheng, Xiang Shi, Pere Barlet-Ros, Albert Cabellos-Aparicio

In the context of DTN, DRL can be leveraged to solve optimization problems without directly impacting the real-world network behavior.

Management reinforcement-learning +1