Now showing items 1-15 of 15

    • 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 ...
    • Challenging the generalization capabilities of Graph Neural Networks for network modeling 

      Suárez-Varela Maciá, José Rafael; Carol Bosch, Sergi; Rusek, Krzysztof; Almasan Puscas, Felician Paul; Arias Vicente, Marta; Barlet Ros, Pere; Cabellos Aparicio, Alberto (Association for Computing Machinery (ACM), 2019)
      Conference report
      Open Access
      Today, network operators still lack functional network models able to make accurate predictions of end-to-end Key Performance Indicators (e.g., delay or jitter) at limited cost. Recently a novel Graph Neural Network (GNN) ...
    • Deep reinforcement learning meets graph neural networks: Exploring a routing optimization use case 

      Almasan Puscas, Felician Paul; Suárez-Varela Maciá, José Rafael; Rusek, Krzysztof; Barlet Ros, Pere; Cabellos Aparicio, Alberto (Elsevier, 2022-12-01)
      Article
      Restricted access - publisher's policy
      Deep Reinforcement Learning (DRL) has shown a dramatic improvement in decision-making and automated control problems. Consequently, DRL represents a promising technique to efficiently solve many relevant optimization ...
    • Desenvolupament d'una aplicació que treballa sobre el protocol LISP 

      Almasan Puscas, Felician Paul (Universitat Politècnica de Catalunya, 2017-04-19)
      Bachelor thesis
      Open Access
      L’increment de les aplicacions que utilitzen la xarxa i dels dispositius connectats a Internet està forçant a buscar una nova forma més òptima i flexible d’encaminar paquets. A conseqüència d’aquest fet, han sorgit nous ...
    • 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 ...
    • Fast traffic engineering by gradient descent with learned differentiable routing 

      Rusek, Krzysztof; Almasan Puscas, Felician Paul; Suárez-Varela Maciá, José Rafael; Cholda, Piotr; Barlet Ros, Pere; Cabellos Aparicio, Alberto (Institute of Electrical and Electronics Engineers (IEEE), 2022)
      Conference lecture
      Open Access
      Emerging applications such as the metaverse, telesurgery or cloud computing require increasingly complex operational demands on networks (e.g., ultra-reliable low latency). Likewise, the ever-faster traffic dynamics will ...
    • 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 ...
    • Leveraging graph neural networks for optimization and traffic compression in network digital twins 

      Almasan Puscas, Felician Paul (Universitat Politècnica de Catalunya, 2023-07-17)
      Doctoral thesis
      Open Access
      (English) In recent years, several industry sectors have adapted the Digital Twin (DT) paradigm to improve the performance of physical systems. This paradigm consists of leveraging computational methods to build high-fidelity ...
    • 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 ...
    • Results and achievements of the ALLIANCE Project: New network solutions for 5G and beyond 

      Careglio, Davide; Spadaro, Salvatore; Cabellos Aparicio, Alberto; Lázaro Villa, José Antonio; Barlet Ros, Pere; Gené Bernaus, Joan M.; Perelló Muntan, Jordi; Agraz Bujan, Fernando; Suárez-Varela Maciá, José Rafael; Pagès Raventós, Albert; Paillissé Vilanova, Jordi; Almasan Puscas, Felician Paul; Domingo Pascual, Jordi; Solé Pareta, Josep (Multidisciplinary Digital Publishing Institute, 2021-09-30)
      Article
      Open Access
      Leaving the current 4th generation of mobile communications behind, 5G will represent a disruptive paradigm shift integrating 5G Radio Access Networks (RANs), ultra-high-capacity access/metro/core optical networks, and ...
    • RouteNet: leveraging graph neural networks for network modeling and optimization in SDN 

      Rusek, Krzysztof; Suárez-Varela Maciá, José Rafael; Almasan Puscas, Felician Paul; Barlet Ros, Pere; Cabellos Aparicio, Alberto (2020-06-05)
      Article
      Open Access
      Network modeling is a key enabler to achieve efficient network operation in future self-driving Software-Defined Networks. However, we still lack functional network models able to produce accurate predictions of Key ...
    • The graph neural networking challenge: a worldwide competition for education in AI/ML for networks 

      Suárez-Varela Maciá, José Rafael; Ferriol Galmés, Miquel; López Brescó, Albert; Almasan Puscas, Felician Paul; Bernárdez Gil, Guillermo; Pujol Perich, David; Rusek, Krzysztof; Bonniot, Loïck; Neumann, Christoph; Schnitzler, François; Taïani, François; Happ, Martin; Barlet Ros, Pere; Cabellos Aparicio, Alberto (2021-07-01)
      Article
      Open Access
      During the last decade, Machine Learning (ML) has increasingly become a hot topic in the field of Computer Networks and is expected to be gradually adopted for a plethora of control, monitoring and management tasks in ...
    • Towards more realistic network models based on Graph Neural Networks 

      Badia Sampera, Arnau; Suárez-Varela Maciá, José Rafael; Almasan Puscas, Felician Paul; Rusek, Krzysztof; Barlet Ros, Pere; Cabellos Aparicio, Alberto (Association for Computing Machinery (ACM), 2019)
      Conference report
      Open Access
      Recently, a Graph Neural Network (GNN) model called RouteNet was proposed as an efficient method to estimate end-to-end network performance metrics such as delay or jitter, given the topology, routing, and traffic of the ...
    • Towards real-time routing optimization with deep reinforcement learning: open challenges 

      Almasan Puscas, Felician Paul; Suárez-Varela Maciá, José Rafael; Wu, Bo; Xiao, Shihan; Barlet Ros, Pere; Cabellos Aparicio, Alberto (Institute of Electrical and Electronics Engineers (IEEE), 2021)
      Conference report
      Open Access
      The digital transformation is pushing the existing network technologies towards new horizons, enabling new applications (e.g., vehicular networks). As a result, the networking community has seen a noticeable increase in ...