TY - GEN
T1 - Can Edge Computing Fulfill the Requirements of Automated Vehicular Services Using 5G Network ?
AU - Ouedraogo, Wendlasida
AU - Araldo, Andrea
AU - Jouaber, Badii
AU - Castel, Hind
AU - Grunblatt, Remy
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024/1/1
Y1 - 2024/1/1
N2 - Communication and computation services supporting Connected and Automated Vehicles (CAVs) are characterized by stringent requirements, in terms of response time and relia-bility. Fulfilling these requirements is crucial for ensuring road safety and traffic optimization. The conceptually simple solution of hosting these services in the vehicles increases their cost (mainly due to the installation and maintenance of computation infrastructure) and may drain their battery excessively. Such disadvantages can be tackled via Multi-Access Edge Computing (MEC), consisting in deploying computation capability in network nodes deployed close to the devices (vehicles in this case), such as to satisfy the stringent CAV requirements. However, it is not yet clear under which conditions MEC can support CAV requirements and for which services. To shed light on this question, we conduct a simulation campaign using well-known open-source simulation tools, namely OMNeT++, Simu5G, Veins, INET, and SUMO. We are thus able to provide a reality check on MEC for CAV, pinpointing what are the computation capacities that must be installed in the MEC, to support the different services, and the amount of vehicles that a single MEC node can support. We find that such parameters must vary a lot, depending on the service considered. This study can serve as a preliminary basis for network operators to plan future deployment of MEC to support CAV.
AB - Communication and computation services supporting Connected and Automated Vehicles (CAVs) are characterized by stringent requirements, in terms of response time and relia-bility. Fulfilling these requirements is crucial for ensuring road safety and traffic optimization. The conceptually simple solution of hosting these services in the vehicles increases their cost (mainly due to the installation and maintenance of computation infrastructure) and may drain their battery excessively. Such disadvantages can be tackled via Multi-Access Edge Computing (MEC), consisting in deploying computation capability in network nodes deployed close to the devices (vehicles in this case), such as to satisfy the stringent CAV requirements. However, it is not yet clear under which conditions MEC can support CAV requirements and for which services. To shed light on this question, we conduct a simulation campaign using well-known open-source simulation tools, namely OMNeT++, Simu5G, Veins, INET, and SUMO. We are thus able to provide a reality check on MEC for CAV, pinpointing what are the computation capacities that must be installed in the MEC, to support the different services, and the amount of vehicles that a single MEC node can support. We find that such parameters must vary a lot, depending on the service considered. This study can serve as a preliminary basis for network operators to plan future deployment of MEC to support CAV.
KW - 5G Simulation
KW - Connected and Auto-mated Vehicles
KW - MEC
U2 - 10.1109/VTC2024-Spring62846.2024.10683522
DO - 10.1109/VTC2024-Spring62846.2024.10683522
M3 - Conference contribution
AN - SCOPUS:85206185672
T3 - IEEE Vehicular Technology Conference
BT - 2024 IEEE 99th Vehicular Technology Conference, VTC2024-Spring 2024 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 99th IEEE Vehicular Technology Conference, VTC 2024-Spring
Y2 - 24 June 2024 through 27 June 2024
ER -