With the development of the Internet of Vehicles (IoV), Parked Vehicle Edge Computing (PVEC) has gradually attracted people's attention. Parked vehicles (PVs) can be exploited as a supplementary computing resource to Mobile Edge Computing (MEC). Using the onboard resources of parked vehicles can effectively improve the security of the blockchain-based internet of vehicles system. However, there are multiple MEC nodes belonging to different service providers and multiple parked vehicles in an area. Due to individual rationality, parked vehicles and MEC nodes will not provide services for free. Therefore, in this paper, we study the interaction of MEC nodes and parked vehicles in blockchain-based parking vehicle edge computing and model it as a two-stage Stackelberg game to optimize the utility of MEC nodes and Parked vehicles. Specifically, we treat the parked vehicle as a leader, set the price of computing resources, treat the MEC node as a follower, and determine the demand for computing resources through the price of the leader. We use ADMM to optimize their utility function to obtain a computing offloading scheme that maximizes system utility. Simulation results show that our scheme can maximize the utility of MEC nodes and Parked vehicles and maximize social welfare.
Computing offloading of multi-MEC nodes in blockchain-based parked vehicle edge computing
Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022) ; 2022 ; Hulun Buir,China
Proc. SPIE ; 12475
2022-11-23
Conference paper
Electronic Resource
English
Balance-Oriented Task Unloading Optimizing Algorithm for Parked Vehicle Edge Computing
British Library Conference Proceedings | 2022
|Balance-Oriented Task Unloading Optimizing Algorithm for Parked Vehicle Edge Computing
Springer Verlag | 2022
|