摘要： 〖JP+1〗在车载自组织网络(VANET)中,车辆高速移动和分布不均导致网络拓扑快速变化、传输路径频繁中断,造成路由效率低下。为此,提出一种适用于城市场景的、基于卡尔曼预测的VANET混合路由算法,每个车辆节点通过部署卡尔曼预测器对邻居节点位置进行预测,通过该预测位置进行路由计算。在GPSR算法贪婪模式和边缘模式的基础上,借助容迟网络(DTN)路由的思想,存储并携带无转发节点的分组直至找到合适的转发节点。仿真结果表明,与GPSR算法和带缓存的GPSR算法相比,该算法在分组投递率和端到端时延方面性能更好。

关键词: 车载自组织网络, 卡尔曼滤波, 位置预测, 混合路由, 地理位置路由, 容迟网络

Abstract: Due to the high mobility and non-uniform distribution of vehicles in Vehicular Ad Hoc Network(VANET),the network topology changes fast and routing paths break frequently,which makes the performance of traditional routing protocols decline seriously.This paper proposes an algorithm Kalman prediction-based hybrid routing which is adequate for city scenario.The algorithm uses Kalman predictor to predict real-time location of vehicles for routing computation.Besides the greedy mode and perimeter mode like Greedy Perimeter Stateless Routing(GPSR),the algorithm takes full use of the mechanism of store-carry-forward in Delay Tolerant Network(DTN) routing.Packets which have no appropriate forwarding nodes are stored and carried by vehicles until the network is well connected,and sends to appropriate forwarding neighbor which benefits delivery performance.Simulation results show that the algorithm has better packet delivery ratio and lower delay compared to GPSR and GPSR with buffer algorithm.

Key words: Vehicular Ad Hoc Network(VANET), Kalman filtering, location prediction, hybrid routing, geographic location routing, Delay Tolerant Network(DTN)

中图分类号: 

• TP393