We developed the N-max algorithm to vertically scale C-V2N services through AI. N-max increases/decreases the number of CPUs that servers use to process the traffic coming from V2N applications as remote driving, cooperative awareness, and hazard warning services. N-max predicts incoming traffic jams in the roads, and increases the number of CPUs to process the increasing demand of V2N traffic in the network. Increasing the number of CPUs upon traffic jams reduces the latency of V2N applications, therefore, vehicles receive the network response on time. Thanks to the N-max vertical scaling, instructions such as remote driving commands are received on time by the vehicle, and the remote driving has a real time synchronization with the remote driver instructions, regardless of the network congestion. N-max performance has been assessed in the aforementioned V2N applications, and it reduced the latency violations down to a 1.09%, 5.82% and 2.52%, respectively.

The developed N-max algorithm assess preemptive vertical scaling in the edge to meet the C-V2N needs upon road-traffic changes such as traffic jams. N-max is an AI-assisted algorithm that reduces the latency violations of critical C-V2N services as remote driving, cooperative awareness, and hazard warning. Reducing the latency violation results in preventing possible collissions of vehicles and other security-related events.