A Dynamic Vehicle-Ranking Approach for Online Virtual Network Embedding in Internet of Vehicles

Abstract

Internet of Vehicles (IoV), a special domain of Internet of Things (IoT), has become an indispensable platform for the success of future intelligent transportation. Virtual Network Embedding (VNE), enabling flexible, cost-effective and on-demand deployments of multiple network service requests on a shared physical infrastructure, has become a technological breakthrough in IoV. Typical VNE problems have been well studied in the data center infrastructure where the physical topology is always static. Recently, researchers have investigated the VNE problem in data center networks while considering IoV demands. However, the VNE problem in IoV environments in which connected moving vehicles serve as substrate nodes to process service requests is still in its infancy. This paper proposes a novel heuristic algorithm for solving the online VNE problem in IoV by efficiently and rapidly ranking available vehicles based upon network attributes, and the knowledge of the preceding mappings. Extensive evaluation results indicate that the proposed solution not only outperforms several existing algorithms, but is also highly practical due to its fast execution time.