Comparison of GPSR and FPSR Algorithms Based on High-Speed Vehicle Information

With the progress of network information technologies, the application of wireless network in high-speed traffic vehicle system has been greatly expanded. However, due to the high-speed movement of nodes, the reliability of high-speed traffic network construction is still relatively low. Therefore, the network data processing of high-speed traffic information has become a hot issue of social concern. In this study, based on the network data system of vehicle information, the greedy perimeter stateless routing (GPSR) algorithm and data forwarding probability strategy based on relevance in vehicular network (FPSR) algorithm were introduced to collect vehicle information from the high-speed traffic examples. The data analysis results of the two algorithms were compared from aspects of the routing stability, delay rate, and success rate. The experimental results showed that the FPSR algorithm was superior in the routing stability and the success rate when the vehicle drove at high speed, while the GPSR algorithm was better in the delay rate and the success rate when the vehicle drove at a low speed. This study can help further understand the performance of the information network, provide technical support for vehicles on high-speed traffic, and provide a theoretical reference for modern intelligent transportation.