Research Article
Optimized Workload Allocation in Vehicular Edge Computing: A Sequential Game Approach
@INPROCEEDINGS{10.1007/978-3-319-78139-6_53, author={Dongdong Ye and Maoqiang Wu and Jiawen Kang and Rong Yu}, title={Optimized Workload Allocation in Vehicular Edge Computing: A Sequential Game Approach}, proceedings={Communications and Networking. 12th International Conference, ChinaCom 2017, Xi’an, China, October 10-12, 2017, Proceedings, Part II}, proceedings_a={CHINACOM}, year={2018}, month={4}, keywords={Vehicular edge computing Workload allocation Sequential Stackelberg game}, doi={10.1007/978-3-319-78139-6_53} }- Dongdong Ye
Maoqiang Wu
Jiawen Kang
Rong Yu
Year: 2018
Optimized Workload Allocation in Vehicular Edge Computing: A Sequential Game Approach
CHINACOM
Springer
DOI: 10.1007/978-3-319-78139-6_53
Abstract
With the development of Vehicle-to-Everything (V2X) communication technologies, Vehicular Edge Computing (VEC) is utilized to speed up the running of vehicular computation workload by deploying VEC servers in close proximity to vehicular terminals. Due to resource limitation of VEC servers, VEC servers are unable to perform a large number of vehicular computation workloads. To improve the performance of VEC servers, we propose a new workload allocation framework where vehicular terminals are divided into Resource Provision Terminals (RPTs) and Resource Demand Terminals (RDTs). In this framework, we design an optimized workload allocation strategy through a sequential Stackelberg game. With the sequential Stackelberg game, a VEC server, RDTs, and RPTs achieve an efficient coordination of the workload allocation. The sequential Stackelberg game is proven to reach two sequential Nash Equilibriums. The simulation results validate the efficiency of the optimized workload allocation strategy.
