Design and Implementation of Propagation-Based Clustering Approach to Improve the Efficiency in Vehicular Sensor Network

Using mobility and connectivity metrics, the PCAIEV model offers an innovative approach to clustering vehicular networks to select a cluster head (CH). A cluster model, which utilizes the segment-based SFS model and the Ada-CSMA/CA algorithm, addresses critical issues related to security message propagation and data transmission. This system is made up of vehicles that have active sensor nodes, passive sensor Nodes (RSS), roadside nodes (RSU), and sink node clusters, which are structured into stable clustered arrangements to minimize link losses. Using the CCS algorithm, which incorporates Circle Variant and Gaussian Variant updates on mobility and connectivity metrics. The Adaptive (CSMA/CA) technique utilizes adaptive delay times that are based on the buffer size to prevent data collisions when transmitting between channels and CMs. A segment-based SFS model using the FV algorithm, which considers node degree, location, transmission probability, and delay, is implemented to send security messages without triggering broadcast storms. The GAPC algorithm improves the clustering process by using beacon messages in the data exchange, which ensures accurate similarity calculations and updating of responsibility and availability values. CCSA is an algorithm that uses chaos theory and foraging behavior to optimize channel selection, considering the relative position of packets, speed, maximum acceleration, node connectivity, and packet delivery ratio. Circular and Gaussian chaos maps are used to select the most accurate route, ensuring better network stability and efficient communications in highly mobile vehicular environments. The proposed PCAIEV protocol shows excellent performance in terms of energy efficiency 425.65 Joules and energy consumption 248.65 Joules, achieving the highest data transmission ratio of 97.12%. Compared to OPRW, it has a lower network throughput of 447.36 Kbps but significantly reduces routing volume by 214.63 packets. PCAIEVs excel in optimizing energy usage and reliable data transmission in VANETs.