A P2P Acceleration Transmission Compensation Cooperative Downloading Approach In VANET

VANET(Vehicular Ad hoc Network) is a special sort of mobile Ad hoc network. As an important extension of IoT technology in the field of intelligent transportation system, VANET performs well not only in terms of traffic safety, intelligent driving, but also has better prospects for the entertainment and mobile office service applications including news, games, and video conferencing. VANET caused widespread concern in the world of research institutions and researchers, has become a hot topic.In real traffic scene, the speed of vehicles on the highway is fast, the deployment of RSU (Roadside Units) is relatively sparse due to the cost, and the communication range of RSU is limited. So vehicles on the road cannot be completely covered by the signal. There is communication blind area, which causes discontinuous communication. When the vehicle node cannot complete the download request within the communication range of one RSU, it has to wait for the next RSU access to continue the unfinished download task. The long delay and intermittent connection lead to poor use experience, which make it difficult for users to enjoy the convenience and entertaining of real-time information exchange. To solve this problem, a method is proposed to assist the download process, which utilizes the same direction vehicles.In this thesis, we first introduce the theory and technology of VANET, discuss the characteristics and application scenarios of VANET, and then a P2P acceleration transmission compensation cooperative downloading approach is presented, based on the model of data downloading within RSU communication coverage areas in highway scenarios. This method makes full use of P2P sharing transmission between vehicles and assistance vehicles carrying the rest of the transmission data to improve system throughput, and integrates data redundancy allocation algorithm to coordinate packet loss rate problem caused by the instability of vehicle speed. The simulation results show that the scheme can improve the accuracy and success rate of assistance vehicles, and avoid the waste of system resources resulting from the excessive choice of vehicles. Although vehicles with redundant data occupy a lot of system resources, the error tolerant rate of the system is improved.