A Dynamic Clustering Method for Maximizing Energy Efficiency in C-V2X Metaverse

The Metaverse can leverage intelligent traffic management technology to simulate the Cellular Vehicle-to-Everything (C-V2X) environment, integrating closely with the Internet of Vehicles due to its advanced connectivity and real-time data processing capabilities. These features make it possible to create a smart transportation system that closely mirrors the real world. Dynamic clustering is an effective network management method for handling the large number of mobile vehicles within the Metaverse, particularly in emergency scenarios where base stations (BSs) may fail. However, frequent changes in network topology due to high-speed vehicles result in unstable clusters and low communication efficiency. In this study, a dynamic clustering algorithm based on motion vector similarity (DA-MVS) is proposed for constructing stable clusters, and an adaptive adjustment clusters strategy is presented based on the change rate of vehicle numbers to improve energy efficiency (EE). Furthermore, we propose an elite chaotic perturbed sparrow search algorithm (ECPSSA) to optimize the EE of the C-V2X. Compared to the multiple baseline algorithm, the successful transmission rate can be improved by up to 76.9%, and the EE is enhanced by 20.97%.