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Dynamic MEC resource management for URLLC in Industry X.0 s..:

, In: 2024 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0 & IoT),

Becattini, Marco ; Carnevali, Laura ; Fontani, Giovanni... - p. 372-376 , 2024

Link: https://doi.org/10.1109/MetroInd4.0IoT61288.2024.10584..

RT 
T1 <cTitle>2024 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0 & IoT)</cTitle>: T1 <Title>Dynamic MEC resource management for URLLC in Industry X.0 scenarios: a quantitative approach based on digital twin networks</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-10584165&Exemplar=1&LAN=DE
				
A1 Becattini, Marco
A1 Carnevali, Laura
A1 Fontani, Giovanni
A1 Paroli, Leonardo
A1 Scommegna, Leonardo
A1 Masoumi, Maryam
A1 de Miguel, Ignacio
A1 Brasca, Fabrizio
YR 2024
SN 2837-0872
K1 Industries
K1 Service robots
K1 Ultra reliable low latency communication
K1 Dynamic scheduling
K1 Real-time systems
K1 Digital twins
K1 Resource management
K1 Industry X.0
K1 Ultra-Reliable and Low Latency Communications (URLLC)
K1 Digital Twin Networks (DTN)
K1 Mobile Edge Computing (MEC)
K1 stochastic modeling and analysis
SP 372
OP 376
LK http://dx.doi.org/https://doi.org/10.1109/MetroInd4.0IoT61288.2024.10584165
DO https://doi.org/10.1109/MetroInd4.0IoT61288.2024.10584165
SF ELIB - SuUB Bremen

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