基于命名数据网络的车联网信息转发策略

Information Forwarding Strategy of Internet of Vehicles in Named Data Network

针对在车联网中由于节点高移动性导致的网络拓扑动态变化问题和传统网络潜在的广播风暴问题,提出一种基于网络拓扑预测的车联网信息转发策略。首先根据车联网中节点性能、车辆运行状态属性、运动轨迹、链路属性等,采用动态网络拓扑演化算法进行拓扑预测,构建当前网络拓扑;再使用最短路径算法构建多源信息转发表,根据信息转发表进行信息转发;最后在转发表失效的情况下,根据节点和链路属性选择最佳邻居节点转发数据,同时,进一步完善基于拓扑预测的内容转发;最后仿真结果表明,与其他转发策略相比,本文所提出的转发策略能有效减少内容获取时延,提高请求命中率。

Aiming at the problem of dynamic change of network topology due to high mobility of nodes and the potential broadcast storm problem of traditional networks in Internet of Vehicles,a network topology prediction-based information forwarding strategy for Internet of Vehicles is proposed.Firstly,according to the performance of nodes,vehicle operation state attributes,movement trajectory,link attributes,etc.in the Internet of Vehicles,a dynamic network topology evolution algorithm is used for topology prediction to construct the current network topology;and then a multi-source information forwarding table is constructed using the shortest path algorithm,and information forwarding is performed according to the information forwarding table.In the case of forwarding table failure,the best neighboring nodes are selected to forward data based on node and link attributes,and at the same time,the topology prediction-based content forwarding is further improved.Simulation results show that compared with other forwarding strategies,the proposed forwarding strategy can effectively reduce the content acquisition delay and improve the request hit rate.