A Contract-Stackelberg Offloading Incentive Mechanism for Vehicular Parked-Edge Computing Networks

摘要

With the development of smart vehicles and computation-intensive vehicular applications, it is a challenge to maintain high performance for vehicles with scarce local computational resources. Mobile Edge Computing (MEC) is a computing paradigm with high potential to improve vehicular services by offloading computation-intensive tasks to the MEC servers. However, as the computational resources of MEC servers are limited, parking lots (PLs) having abundant idle computational resources should be utilized. We introduce a new computing paradigm, named by Vehicular Parked-Edge Computing (VPEC). We formulate a three-stage contract-stackelberg offloading incentive mechanism to describe this problem. The PLs are classified into different types according to their idle computational resources, and parking lot agent (PLA) offers different contracts to different types of PLs. The optimal problem is designed to maximize the utilities of vehicles, operator and PLA. We use backward induction method to solve this three-stage problem, and give the closed-form expressions of the optimal strategies for each stage. Simulation results demonstrate the feasibility of the proposed incentive mechanism and reveal the changing trend of optimal strategies in each stage when traffic density changes.