Dynamic MEC resource management for URLLC in Industry X.0 scenarios: a quantitative approach based on digital twin networks. Becattini, M., Carnevali, L., Fontani, G., Paroli, L., Scommegna, L., Masoumi, M., de Miguel, I., & Brasca, F. In IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd4.0 \& IoT 2024, Firenze, Italy, May 29-31, 2024, pages 372–376, 2024. IEEE.
Dynamic MEC resource management for URLLC in Industry X.0 scenarios: a quantitative approach based on digital twin networks [link]Paper  doi  bibtex   
@inproceedings{DBLP:conf/metroi/BecattiniCFPSMMB24,
    author = "Becattini, Marco and Carnevali, Laura and Fontani, Giovanni and Paroli, Leonardo and Scommegna, Leonardo and Masoumi, Maryam and de Miguel, Ignacio and Brasca, Fabrizio",
    title = "Dynamic {MEC} resource management for {URLLC} in Industry {X.0} scenarios: a quantitative approach based on digital twin networks",
    booktitle = "{IEEE} International Workshop on Metrology for Industry 4.0 and IoT, MetroInd4.0 {\\&} IoT 2024, Firenze, Italy, May 29-31, 2024",
    pages = "372--376",
    publisher = "{IEEE}",
    year = "2024",
    url = "https://doi.org/10.1109/MetroInd4.0IoT61288.2024.10584165",
    doi = "10.1109/METROIND4.0IOT61288.2024.10584165",
    timestamp = "Mon, 15 Jul 2024 15:28:30 +0200",
    biburl = "https://dblp.org/rec/conf/metroi/BecattiniCFPSMMB24.bib",
    bibsource = "dblp computer science bibliography, https://dblp.org"
}

Downloads: 0