A Dynamic Evolution Mechanism for IoV Community in an Urban Scene

Existing work on the Internet-of-Vehicles (IoV) community mainly focuses on the detection of IoV community using static network detection and evolution methods of complex networks. These methods are prone to over-centralization, high computational complexity, and poor stability during the evolution of a community. In this work, we present an IoV community model and its evolution mechanism in an urban scene. More specifically, we first propose an IoV community detection model based on node similarity merging. Then, we use a network increment-based strategy to analyze node increment, edge increment, and weight increment. Finally, we give a dynamic evolution mechanism of an IoV community. Simulation-based experimental evaluation results show that the proposed mechanism achieves better real-time performance and accuracy than existing methods.