Game-Theoretic Dependent Task Offloading and Resource Pricing in Vehicular Edge Computing

This paper proposes a Stacklberg game-based Dependent task Offloading and resource Pricing framework (SDOP), where vehicles partially offload their dependent substaks to the SDN controller and pays corresponding fees. Firstly, we model the interaction between the SDN controller and vehicles as a Stackelberg game, where both parties wish to maximize their utility. Then, we employ the backward induction approach to analyze the investigated problem, and prove the existence and uniqueness of Nash and Stackelberg equilibrium. Next, we propose a Gradient Ascent Plus Genetic algorithm (GAPG) to solve the considered problem. Finally, extensive simulation results show that the proposed GAPG outperforms other baseline schemes under various scenarios.