Research Article
Resource Allocation Algorithms of Vehicle Networks with Stackelberg Game
@INPROCEEDINGS{10.1007/978-3-030-48513-9_18, author={Ying Zhang and Guang-Shun Li and Jun-Hua Wu and Jia-He Yan and Xiao-Fei Sheng}, title={Resource Allocation Algorithms of Vehicle Networks with Stackelberg Game}, proceedings={Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications. 9th EAI International Conference, CloudComp 2019, and 4th EAI International Conference, SmartGIFT 2019, Beijing, China, December 4-5, 2019, and December 21-22, 2019}, proceedings_a={CLOUDCOMP}, year={2020}, month={6}, keywords={Internet of Vehicles Edge computing Stackelberg game Wireless resource allocation Nash equilibrium}, doi={10.1007/978-3-030-48513-9_18} }- Ying Zhang
Guang-Shun Li
Jun-Hua Wu
Jia-He Yan
Xiao-Fei Sheng
Year: 2020
Resource Allocation Algorithms of Vehicle Networks with Stackelberg Game
CLOUDCOMP
Springer
DOI: 10.1007/978-3-030-48513-9_18
Abstract
With the emergence and development of the Internet of Vehicles (IoV), higher demands are placed on the response speed and ultra-low delay of the vehicle. Cloud computing services are not friendly to reducing latency and response time. Mobile Edge Computing (MEC) is a promising solution to this problem. In this paper, we introduce MEC into the IoV to propose a specific vehicle edge resource management framework, which consists of fog nodes (FN), data service agents (DSA), and cars. We proposed a dynamic service area partitioning algorithm that enables the DSA to adjust the service area and provide a more efficient service for the vehicle. A resource allocation framework based on Stackelberg game model is proposed to analyze the pricing problem of FN and data resource strategy of DSA. We use the distributed iterative algorithm to solve the problem of game equilibrium. Our proposed resource management framework is finally verified by numerical results, which show that the allocation efficiency of FN resources among the cars is ensured, and we also get a subgame perfect nash equilibrium.