An online auction mechanism for double time-varying constraints in vehicular edge computing
Xiao Peng, Jixian Zhang · 2022
Real-time resource allocation has become a hot topic in vehicular edge computing environment. However, vehicle equipment with limited computing capability cannot meet the Quality of service of computation intensive and delay sensitive vehicle applications. Moreover, in most studies, the deployment constraints in edge computing and users’ resource demand are static, which is inconsistent with real scenarios. In this paper, an online auction mechanism with double time-varying constraints is proposed to solve the resource allocation problem in a vehicular edge computing environment. Specifically, we first formulate the resource allocation problem between edge computing servers (ECSs) and vehicles as a novel integer programming model with time-varying deployment constraint and time-varying resource demand. Then, we design an online auction mechanism based on heuristics. In the resource allocation algorithm, a matching model and dominant-resource-proportion strategy are adopted to improve the resource utilization and social welfare. Simultaneously, a payment pricing algorithm based on the dichotomy is proposed. Finally, we prove that the online mechanism is individually rational and truthful. The experimental results demonstrate that our online mechanism has higher social welfare and resource utilization than existing research.