With the developments of the Internet of Vehicles (IoV) from 4G to 5G, vehicle-to-infrastructure (V2I) communications are becoming attractive for vehicle users (VUEs) to obtain diverse cloud service through base stations (BSs). To tackle V2I link deterioration caused by blockage and out-of-coverage cases, multi-hop V2X routing with both vehicle-to-vehicle (V2V) and V2I links needs to be investigated. However, traditional routing reacts to statistical or real-time information, which may suffer link degradation during path switchover in fast-changing vehicular networks. Predictive routing protocols take timely actions by forecasting link connectivity, but they fail to satisfy specific QoS requirements. Low robustness to link failures is also incurred without considering imperfect prediction. To build continual paths between VUEs and BSs for QoS provision of cloud service, a robust predictive routing framework (ROPE) is proposed with three major components: 1) an early warning scheme detects V2I link deterioration in advance via predicting vehicle mobility and link signal strength to facilitate seamless path switchover; 2) a virtual routing mechanism finds top3 paths that have the highest path strength and satisfy the connectivity and hop count constraints based on the prediction results to fulfill QoS requirements of cloud service; 3) a path verification protocol checks availability and quality of the top3 paths shortly before switchover and activates one qualified path for switchover to ensure routing robustness. We implement ROPE in a simulation framework incorporating real-world urban maps, microscopic traffic generation, geometry-based channel modeling, and offline data analysis as well as online inference. Extensive simulations demonstrate the superiority of ROPE over direct V2I communications and a connectivity-based predictive routing protocol under various scenarios.

翻译：随着车联网从4G向5G演进，车辆用户通过基站获取多样化云服务的车辆到基础设施通信正变得极具吸引力。为应对由遮挡和覆盖盲区导致的V2I链路质量恶化，需研究融合车辆到车辆链路与V2I链路的多跳V2X路由技术。然而，传统路由方案依赖统计或实时信息进行响应，在快速变化的车联网环境中进行路径切换时易遭遇链路性能劣化。预测性路由协议通过预判链路连通性及时采取行动，却难以满足特定服务质量需求。由于未考虑预测误差，此类协议对链路失效的鲁棒性亦显不足。为在车辆用户与基站间构建持续可用的云服务保障路径，本文提出鲁棒预测路由框架，其包含三大核心组件：1）预警机制通过预测车辆移动性与链路信号强度，提前检测V2I链路劣化趋势，为无缝路径切换提供支持；2）虚拟路由机制依据预测结果，在满足连通性与跳数约束条件下筛选路径强度最高的三条候选路径，以满足云服务服务质量需求；3）路径验证协议在切换前即时检测候选路径的可用性与质量，并激活符合条件的路径执行切换，确保路由鲁棒性。我们在融合真实城市地图、微观交通生成、几何信道建模、离线数据分析与在线推理的仿真框架中实现了该框架。大量仿真实验表明，在不同场景下该框架均优于直接V2I通信方案及基于连通性的预测路由协议。