Zobrazeno 1 - 10
of 194
pro vyhledávání: '"Sánchez-Macián A"'
Autor:
Navarro, Alejandro Leonardo García, Koneva, Nataliia, Sánchez-Macián, Alfonso, Hernández, José Alberto, Goyanes, Manuel
In social sciences, researchers often face challenges when conducting large-scale experiments, particularly due to the simulations' complexity and the lack of technical expertise required to develop such frameworks. Agent-Based Modeling (ABM) is a co
Externí odkaz:
http://arxiv.org/abs/2411.07038
Autor:
Arpanaei, F., Natalino, C., Zefreh, M. Ranjbar, Yan, S., Rabbani, H., Brandt-Pearce, Maite, Fernandez-Palacios, J. P., Rivas-Moscoso, J. M., de Dios, O. Gonzalez, Hernandez, J. A., Sanchez-Macian, A., Larrabeiti, D., Monti, P.
In the ultra-low inter-core crosstalk working zone of terrestrial multi-band and multi-core fiber (MCF) elastic optical networks (EONs), the ICXT in all channels of all cores remains below the ICXT threshold of the highest modulation format level (64
Externí odkaz:
http://arxiv.org/abs/2411.03772
Web application pentesting is a crucial component in the offensive cybersecurity area, whose aim is to safeguard web applications and web services as the majority of the web applications are mounted in publicly accessible web environments. This metho
Externí odkaz:
http://arxiv.org/abs/2410.12422
Autor:
Teng, Yiran, Natalino, Carlos, Arpanaei, Farhad, Sánchez-Macián, Alfonso, Monti, Paolo, Yan, Shuangyi, Simeonidou, Dimitra
We propose a DRL-assisted approach for service provisioning in multi-band elastic optical networks. Our simulation environment uses an accurate QoT estimator based on the GN/EGN model. Results show that the proposed approach reduces request blocking
Externí odkaz:
http://arxiv.org/abs/2408.03221
Autor:
Sánchez-Macián, Alfonso, Koneva, Nataliia, Quagliotti, Marco, Rivas-Moscoso, José M., Arpanaei, Farhad, Hernández, José Alberto, Fernández-Palacios, Juan P., Zhang, Li, Riccardi, Emilio
Model networks and their underlying topologies have been used as a reference for techno-economic studies for several decades. Existing reference topologies for optical networks may cover different network segments such as backbone, metro core, metro
Externí odkaz:
http://arxiv.org/abs/2408.01721
Autor:
Navarro, Alejandro L. García, Koneva, Nataliia, Sánchez-Macián, Alfonso, Hernández, José Alberto
Python has gained widespread popularity in the fields of machine learning, artificial intelligence, and data engineering due to its effectiveness and extensive libraries. R, on its side, remains a dominant language for statistical analysis and visual
Externí odkaz:
http://arxiv.org/abs/2407.14695
Autor:
de Quinto, C., Navarro, A., Otero, G., Koneva, N., Hernández, J. A., Quagliotti, M., Sánchez-Macian, A., Arpanaei, F., Reviriego, P., de Dios, Ó. González, Rivas-Moscoso, J. M., Riccardi, E., Larrabeiti, D.
With the advent of next-generation AR/VR headsets, many of them with affordable prices, telecom operators have forecasted an explosive growth of traffic in their networks. Penetration of AR/VR services and applications is estimated to grow exponentia
Externí odkaz:
http://arxiv.org/abs/2407.07686
Autor:
Koneva, Nataliia, Sánchez-Macián, Alfonso, Hernández, José Alberto, Arpanaei, Farhad, de Dios, Óscar González
Accurate estimation of queuing delays is crucial for designing and optimizing communication networks, particularly in the context of Deterministic Networking (DetNet) scenarios. This study investigates the approximation of Internet queuing delays usi
Externí odkaz:
http://arxiv.org/abs/2406.16452
Autor:
Navarro, A. L. García, Koneva, Nataliia, Sánchez-Macián, Alfonso, Hernández, José Alberto, de Dios, Óscar González, Rivas-Moscoso, J. M.
Publikováno v:
The 28th International Conference on Optical Network Design and Modelling (ONDM 2024)
This article provides a methodology and open-source implementation of Reinforcement Learning algorithms for finding optimal routes in a packet-optical network scenario. The algorithm uses measurements provided by the physical layer (pre-FEC bit error
Externí odkaz:
http://arxiv.org/abs/2406.12602
Publikováno v:
The 28th International Conference on Optical Network Design and Modelling (ONDM 2024)
The power of Machine Learning and Artificial Intelligence algorithms based on collected datasets, along with the programmability and flexibility provided by Software Defined Networking can provide the building blocks for constructing the so-called Ze
Externí odkaz:
http://arxiv.org/abs/2406.12594