The trade-offs between Fog Processing and Communications in latency-sensitive Vehicular Fog Computing

Abstract

In a vehicular fog computing paradigm, connected autonomous vehicles are envisioned as processing nodes (i.e. fog nodes) so that end-devices may offload processing tasks to them. As such, both local and distributed processing on fog nodes will depend heavily on wireless network conditions and the current traffic demand. In this work, we investigate the trade-offs on the operation of fog nodes under different vehicle densities and network conditions and formalize a Time Constrained One-Shot Open First Price Auction for resource allocation in vehicular fog computing. Through a large-scale simulation study, we assess important aspects of the performance of fog nodes in Vehicular Fog Computing. We show that current wireless network standards may dictate the limits of processing despite the availability of processing power of fog nodes. Our results indicate the existence of trade-offs on the operation of fog nodes regarding message overhead and processing redundancy to achieve high task completion ratio. Finally, we evaluate the social welfare distribution of the task allocation achieved using the auction where higher message rates lead to higher costs.