A Game Theoretical Priority-Aware R2V Task Offloading Framework for Vehicular Fog Networks
Kinda Khawam, Maurice Khabbaz, Joe Saad · IEEE Open Journal of the Communications Society · 2025
Modern vehicles, equipped with advanced digital infrastructure, are transforming from mere transportation units to powerful mobile servers. This trend, coupled with the rise of mobile edge computing (MEC), presents a unique opportunity to leverage vehicles as temporary computing resources. Roadside Units (RSUs) can then offload urgent tasks to passing vehicles, enabling ubiquitous connectivity and low-latency services. However, efficient task offloading remains a challenge. This paper proposes a two-level resource management framework for Priority-Aware RSU-to-Vehicle (PA-R2V) Task Offloading (PA-R2VTO) to address this issue. The first level utilizes a two-stage Stackelberg game to incentivize vehicles within RSU coverage to allocate a portion of their computing resources. The second level focuses on task assignment to participating vehicles. Two computation modes are considered: serial and parallel. Serial computation leverages a Multiple Knapsack Problem (MKP) formulation to prioritize tasks based on deadlines, while parallel computation employs a non-cooperative congestion game model. Both approaches are compared against the traditional Earliest Deadline First (EDF) scheduling algorithm. Extensive simulations validate the framework’s effectiveness, paving the way for a more tangible realization of the Vehicle-as-a-Resource (VaaR) concept.