Dissatisfaction Feedback and Stackelberg Game-Based Task Offloading Mechanism for Parked Vehicle Edge Computing

Considering the limited computing power of Mobile Edge Computing (MEC) servers and the emergence of Vehicular Ad-Hoc Networks (VANETs), we employ the computing paradigm known as Parked Vehicle Edge Computing (PVEC) to leverage the computational capabilities of idle vehicles, thereby enhancing the overall computing performance of these vehicles. We establish a multi-stage Stackelberg game model, which captures the interactions among the requester (RV), the service provider (SP), and the parked vehicles (PV). In order to incentivize parked vehicles to provide computing power, we design a dissatisfaction feedback mechanism. To optimize the system and maximize the relative benefits of all stakeholders, we formulate an optimization problem to find an optimal pricing scheme that guides task allocation and resource utilization. We employ reverse induction and gradient descent to solve this problem. Simulation results demonstrate the effectiveness of the dissatisfaction feedback mechanism and provide insights into the changing trends of optimal strategies at each stage as the task density increases. These findings contribute to the understanding of PVEC and offer guidance for real-world task offloading scenarios.

I. Introduction

With the popularization of smart mobile devices and the development of computationally intensive applications, the task of enhancing device computing performance poses a significant challenge given the limitations of mobile device computing power. In recent years, Mobile Edge Computing (MEC) has offered a promising solution by offloading computationally intensive tasks to MEC servers, harnessing the benefits of heightened computational efficiency and reduced communication latency [1]. Nonetheless, the computing resources of edge servers remain limited, making it difficult to ensure the provision of Quality of Service (QoS) when offloading compute-intensive tasks to these constrained servers. Thus, it becomes imperative to augment the resource capacity of edge servers by effectively utilizing the idle resources of existing network entities. A noteworthy observation is the emergence of Vehicular Ad-Hoc Networks (VANETs), wherein vehicles possess abundant idle computing resources that can be harnessed to establish a novel computing paradigm for task offloading, known as Parked Vehicle Edge Computing (PVEC) [2]. This paradigm serves to enhance the communication and computing capabilities of urban areas.