HP-MMFA: Mobility-Aware Min-Max Resource Allocation for Vehicular Cloud Computing

With the rapid development of communication technologies in Autonomous Vehicular Clouds (AVC), modern vehicles possess increasing amounts of idle storage and computing resources that are often unused and can be shared with nearby vehicles to support different services. In vehicular cloud computing, many services are elastic, which means they can continue operating with partial resources, although with reduced quality or slower execution. Examples include video streaming, data upload, sensing data transfer, and non-urgent computation tasks. For such services, it is more practical to guarantee a minimum acceptable resource level and then provide additional bandwidth when more resources are available.

For this reason, Min-Max resource allocation is suitable for elastic vehicular services. Each admitted Client Vehicle (CV) first receives its minimum required bandwidth so that the service can continue operating. The remaining bandwidth is then distributed progressively up to the maximum requested bandwidth of each CV. This permits more vehicles to remain in service under limited resources. Therefore, elastic services benefit from the Min-Max method by improving service continuity, resource utilization, and fairness.

The main contributions are:
A mobility-feasibility model considering RSU residence time and CV–SV link duration.
HP-MMFA, which prioritizes feasible handoff tasks with smaller mobility slack before Min-Max allocation.
Comparison of B-MMFA, LP-MMFA, and HP-MMFA using 100 simulation runs.