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Results: 57
Number of items: 57
  • Hsu, C. S.-H., De Vleeschauwer, D., & Papagianni, C. (2023). SLA Decomposition for Network Slicing: A Deep Neural Network Approach. IEEE Networking Letters, 5(4), 294-298. https://doi.org/10.1109/LNET.2023.3310359
  • Open Access
    Hsu, CS.-H., Martín-Pérez, J., Papagianni, C., & Grosso, P. (2023). V2N Service Scaling with Deep Reinforcement Learning. In K. Akkaya, O. Festor, C. Fung, M. A. Rahman, L. Zambenedetti Granville, & C. R. Paula dos Santos (Eds.), Proceedings of IEEE/IFIP Network Operations and Management Symposium 2023: 8-12 May 2023 : NOMS (pp. 725-729). IEEE. https://doi.org/10.1109/NOMS56928.2023.10154358
  • Open Access
    Papadopoulos, K., Papadimitriou, P., & Papagianni, C. (2023). Deterministic and Probabilistic P4-Enabled Lightweight In-Band Network Telemetry. IEEE Transactions on Network and Service Management, 20(4), 4909 - 4922. https://doi.org/10.1109/TNSM.2023.3301839
  • Gombos, G., Mouw, M., Laki, S., Papagianni, C., & De Schepper, K. (2022). Active Queue Management on the Tofino programmable switch: The (Dual)PI2 case. In ICC 2022 - IEEE International Conference on Communications: Seoul, South Korea, 16-20 May 2022 (pp. 1685-1691). IEEE. https://doi.org/10.1109/ICC45855.2022.9838674
  • de Almeida, L. C., Matos, G., Pasquini, R., Papagianni, C., & Verdi, F. L. (2022). iRED: Improving the DASH QoS by dropping packets in programmable data planes. In M. Charalambides, P. Papadimitriou, W. Cerroni, S. Kanhere, L. Mamatas, C. Raniery dos Santos, & V. Fulber-Garcia (Eds.), 2022 18th International Conference on Network and Service Management (CNSM 2022): Thessaloniki, Greece, 31 October-4 November 2022 (pp. 136-144). International Federation for Information Processing. https://doi.org/10.23919/CNSM55787.2022.9964949
  • Open Access
    Martín-Pérez, J., Kondepu, K., De Vleeschauwer, D., Reddy, V., Guimarães, C., Sgambelluri, A., Valcarenghi, L., Papagianni, C., & Bernardos, C. J. (2022). Dimensioning V2N Services in 5G Networks through Forecast-based Scaling. IEEE Access, 10, 9587-9602. https://doi.org/10.1109/ACCESS.2022.3142346
  • Velasco, L., Signorelli, M., González de Dios, O., Papagianni, C., Bifulco, R., Vegas Olmos, J. J., Pryor, S., Carrozzo, G., Schulz-Zander, J., Bennis, M., Martinez, R., Cugini, F., Salvadori, C., Lefebvre, V., Valcarenghi, L., & Ruiz, M. (2021). End-to-End Intent-Based Networking. IEEE Communications Magazine, 59(10), 106-112. https://doi.org/10.1109/MCOM.101.2100141
  • Wassing, T. J., De Vleeschauwer, D., & Papagianni, C. (2021). A Machine Learning Approach for Service Function Chain Embedding in Cloud Datacenter Networks. In 2021 IEEE 10th International Conference on Cloud Networking (CloudNet 2021): virtual conference, 8-10 November 2021 (pp. 26-32). IEEE. https://doi.org/10.1109/CloudNet53349.2021.9657124
  • De Vleeschauwer, D., Papagianni, C., & Walid, A. (2021). Decomposing SLAs for Network Slicing. IEEE Communications Letters, 25(3), 950-954. https://doi.org/10.1109/LCOMM.2020.3033042
  • Guimarães, C., Li, X., Papagianni, C., Mangues-Bafalluy, J., Contreras, L. M., Garcia-Saavedra, A., Brenes, J., San Cristobal, D., Alonso, J., Zabala, A., Kainulainen, J.-P., Mourad, A., Lorenzo, M., & Bernardos, C. J. (2021). Public and Non-Public Network Integration for 5Growth Industry 4.0 Use Cases. IEEE Communications Magazine, 59(7), 108-114. https://doi.org/10.1109/MCOM.001.2000853
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