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Fixed edge processing has become a key feature of 5G networks, while playinga key role in reducing latency, improving energy efficiency and introducingflexible compute resource utilization on-demand with added cost savings.Autonomous vehicles are expected to possess significantly more on-boardprocessing capabilities and with improved connectivity. Vehicles continue to beused for a fraction of the day, and as such there is a potential to increaseprocessing capacity by utilizing these resources while vehicles are inshort-term and long-term car parks, in roads and at road intersections. Suchcar parks and road segments can be transformed, through 6G networks, intovehicular fog clusters, or Fogbanks, that can provide processing, storage andsensing capabilities, making use of underutilized vehicular resources. Weintroduce the Fogbanks concept, outline current research efforts underway invehicular clouds, and suggest promising directions for 6G in a world whereautonomous driving will become commonplace. Moreover, we study the processingallocation problem in cloud-based Fogbank architecture. We solve this problemusing Mixed Integer Programming (MILP) to minimize the total power consumptionof the proposed architecture, taking into account two allocation strategies,single allocation of tasks and distributed allocation. Finally, we describeadditional future directions needed to establish reliability, security,virtualisation, energy efficiency, business models and standardization.

Fogbanks: Future Dynamic Vehicular Fog Banks for Processing, Sensing and Storage in 6G