Now showing items 1-10 of 10

    • Accelerating deep reinforcement learning for digital twin network optimization with evolutionary strategies 

      Güemes Palau, Carlos; Almasan Puscas, Felician Paul; Xiao, Shihan; Cheng, Xiangle; Shi, Xiang; Barlet Ros, Pere; Cabellos Aparicio, Alberto (Institute of Electrical and Electronics Engineers (IEEE), 2022)
      Conference report
      Open Access
      The recent growth of emergent network applications (e.g., satellite networks, vehicular networks) is increasing the complexity of managing modern communication networks. As a result, the community proposed the Digital Twin ...
    • Building a Digital Twin for network optimization using graph neural networks 

      Ferriol Galmés, Miquel; Suárez-Varela Maciá, José Rafael; Paillissé Vilanova, Jordi; Shi, Xiang; Xiao, Shihan; Cheng, Xiangle; Barlet Ros, Pere; Cabellos Aparicio, Alberto (2022-11-09)
      Article
      Open Access
      Network modeling is a critical component of Quality of Service (QoS) optimization. Current networks implement Service Level Agreements (SLA) by careful configuration of both routing and queue scheduling policies. However, ...
    • ENERO: Efficient real-time WAN routing optimization with Deep Reinforcement Learning 

      Almasan Puscas, Felician Paul; Xiao, Shihan; Cheng, Xiangle; Shi, Xiang; Barlet Ros, Pere; Cabellos Aparicio, Alberto (2022-09-04)
      Article
      Open Access
      Wide Area Networks (WAN) are a key infrastructure in today’s society. During the last years, WANs have seen a considerable increase in network’s traffic and network applications, imposing new requirements on existing network ...
    • FlowDT: A Flow-aware Digital Twin for computer networks 

      Ferriol Galmés, Miquel; Cheng, Xiangle; Shi, Xiang; Xiao, Shihan; Barlet Ros, Pere; Cabellos Aparicio, Alberto (Institute of Electrical and Electronics Engineers (IEEE), 2022)
      Conference report
      Open Access
      Network modeling is an essential tool for network planning and management. It allows network administrators to explore the performance of new protocols, mechanisms, or optimal configurations without the need for testing ...
    • Graph neural networks for communication networks: context, use cases and opportunities 

      Suárez-Varela Maciá, José Rafael; Almasan Puscas, Felician Paul; Ferriol Galmés, Miquel; Rusek, Krzysztof; Geyer, Fabien; Cheng, Xiangle; Shi, Xiang; Xiao, Shihan; Scarselli, Franco; Cabellos Aparicio, Alberto; Barlet Ros, Pere (2023-05)
      Article
      Open Access
      Graph neural networks (GNN) have shown outstanding applications in fields where data is essentially represented as graphs (e.g., chemistry, biology, recommendation systems). In this vein, communication networks comprise ...
    • MAGNNETO: A graph neural network-based multi-agent system for traffic engineering 

      Bernárdez Gil, Guillermo; Suárez-Varela Maciá, José Rafael; López Brescó, Albert; Shi, Xiang; Xiao, Shihan; Cheng, Xiangle; Barlet Ros, Pere; Cabellos Aparicio, Alberto (2023-04)
      Article
      Open Access
      Current trends in networking propose the use of Machine Learning (ML) for a wide variety of network optimization tasks. As such, many efforts have been made to produce ML-based solutions for Traffic Engineering (TE), which ...
    • Network digital twin: context, enabling technologies, and opportunities 

      Almasan Puscas, Felician Paul; Ferriol Galmés, Miquel; Paillissé Vilanova, Jordi; Suárez-Varela Maciá, José Rafael; Perino, Diego; Lopez, Diego; Pastor Perales, Antonio Agustín; Harvey, Paul; Ciavaglia, Laurent; Wong, Leon; Xiao, Shihan; Ram, Vishnu; Shi, Xiang; Cheng, Xiangle; Cabellos Aparicio, Alberto; Barlet Ros, Pere (2022-11)
      Article
      Open Access
      The proliferation of emergent network applications (e.g., telesurgery, metaverse) is increasing the difficulty of managing modern communication networks. These applications entail stringent network requirements (e.g., ...
    • Performance-oriented digital twins for packet and optical networks 

      Cabellos Aparicio, Alberto; Janz, Christopher; Almasan Puscas, Felician Paul; Ferriol Galmés, Miquel; Barlet Ros, Pere; Paillissé Vilanova, Jordi; Xiao, Shihan; Shi, Xiang; Cheng, Xiangle; Guo, Aihua; Perino, Diego; Lopez, Diego; Pastor Perales, Antonio Agustín (2023-10-23)
      Research report
      Open Access
      This draft introduces the concept of a Network Digital Twin (NDT), including the architecture as well as the interfaces. Then two specific instances of the NDT are introduced, the first one for packet networks. This ...
    • RouteNet-Erlang: A graph neural network for network performance evaluation 

      Ferriol Galmés, Miquel; Rusek, Krzysztof; Suárez-Varela Maciá, José Rafael; Xiao, Shihan; Shi, Xiang; Cheng, Xiangle; Wu, Bo; Barlet Ros, Pere; Cabellos Aparicio, Alberto (Institute of Electrical and Electronics Engineers (IEEE), 2022)
      Conference report
      Open Access
      Network modeling is a fundamental tool in network research, design, and operation. Arguably the most popular method for modeling is Queuing Theory (QT). Its main limitation is that it imposes strong assumptions on the ...
    • RouteNet-Fermi: network modeling with graph neural networks 

      Ferriol Galmés, Miquel; Paillissé Vilanova, Jordi; Suárez-Varela Maciá, José Rafael; Rusek, Krzysztof; Xiao, Shihan; Shi, Xiang; Cheng, Xiangle; Barlet Ros, Pere; Cabellos Aparicio, Alberto (Institute of Electrical and Electronics Engineers (IEEE), 2023-12)
      Article
      Open Access
      Network models are an essential block of modern networks. For example, they are widely used in network planning and optimization. However, as networks increase in scale and complexity, some models present limitations, such ...