稀疏场景下基于网络编码和RSU数据传输的研究

摘要

车载自组织网中数据传输的场景主要包括车辆密集的城市道路场景和车辆稀疏的偏远地区,目前大多数研究针对的是车辆密集场景下数据传输.在车辆稀疏的车载自组织网中,车辆节点间相遇的概率受限,因此数据传输面临信道负载大、传输延时高、带宽利用率低等挑战.为了提高数据包在稀疏场景下传输性能,提出了基于代间渐进编码技术和RSU的传输策略RORLNC,通过各个编码代之间的渐进编码操作,可有效防止因丢包引起编码数据包无法被解码.另外借助RSU寻找最佳转发车辆节点,可有效避免编码数据包长期无法被转发.用NS-2和MOVE软件进行仿真实验.实验结果证明RORLNC比现有的DDR算法具有较高的吞吐率和较低的平均转发延迟.%The scene of data transmission in VANET mainly includes vehicle intensive urban road scenes and vehicle sparsely in remote areas.Nowadays, most of the research is focused on the data transmission in the vehicle intensive scene.In the sparse VANET, the probability of meeting between the nodes of the vehicle is limited, so the data transmission faces the challenges of large channel load, high transmission delay and low bandwidth utilization.In order to improve the transmission performance of the packet in the sparse scene, a transmission strategy RORLNC based on the inter-generation gradual network coding and RSU is proposed.Through the coding between the various code generation operation, can effectively prevent packet loss caused by the encoded data packet can''t be decoded.In addition, the best forwarding node can be found by RSU, which can avoid the long-term failure to forward the encoded data packet.The simulation experiment is carried out with NS-2 and MOVE software, and the experimental results show that RORLNC has higher throughput and lower average forwarding delay than the existing DDR algorithm.