  Development of autonomous and self-driving vehicles requires agile and
reliable services to manage hazardous road situations. Vehicular Network is the
medium that can provide high-quality services for self-driving vehicles. The
majority of service requests in Vehicular Networks are delay intolerant (e.g.,
hazard alerts, lane change warning) and require immediate service. Therefore,
Vehicular Networks, and particularly, Vehicle-to-Infrastructure (V2I) systems
must provide a consistent real-time response to autonomous vehicles. During
peak hours or disasters, when a surge of requests arrives at a Base Station, it
is challenging for the V2I system to maintain its performance, which can lead
to hazardous consequences. Hence, the goal of this research is to develop a V2I
system that is robust against uncertain request arrivals. To achieve this goal,
we propose to dynamically allocate service requests among Base Stations. We
develop an uncertainty-aware resource allocation method for the federated
environment that assigns arriving requests to a Base Station so that the
likelihood of completing it on-time is maximized. We evaluate the system under
various workload conditions and oversubscription levels. Simulation results
show that edge federation can improve robustness of the V2I system by reducing
the overall service miss rate by up to 45%.
