车载自组网信息交互最大流传输优化策略

Optimization Strategy of Information Interaction Maximum Flow Transmission in Vehicle Ad Hoc Network

在智能车联网中,多用户请求大量数据资源时存在传输不稳定的问题。为此,在车辆节点移动环境下提出集合覆盖最大流(SCMF)算法。利用集合覆盖方法考虑更多请求细节并分析最优化随机需求模型,优化信息资源共享和数据传输过程,保证车辆与无线访问节点及车辆之间信息交互以最大流效率传输,快速稳定地处理客户大数据资源请求。实验结果表明,SCMF算法能够以较少的网络开销和传输延时获得较高的传输效率,提高网络资源利用率和综合性能。

Aiming at the transmission instability problem when multiple users request a large number ot uata resources in intelligent vehicle network, this paper proposes a Set Covering Maximum Flow （SCMF） algorithm in mobile vehicle node environment. It uses set covering method to consider more request details and analyzes optimal stochastic demand model, which optimizes information resource sharing and data transmission process, guarantees vehicle information interaction between vehicle and wireless Access Point （AP） nodes with maximum flow efficiency transmission, and processes the customer＇ s big data resource request quickly and steadily. Experimental results show that the SCMF algorithm can obtain higher transmission efficiency with lower network overhead and transmission delay. It improves the utilization of network resources and comprehensive performance.