基于路径探索的车载自组网贪婪路由算法

为了提高城市中车辆间信息的传输效率,实现车辆间的信息共享,针对目前车载自组网(VANET)中基于地理位置转发的多跳单播路由算法没有考虑城市场景的特殊性,不能很好地适应城市中车辆的高度动态性,使车辆之间的数据包可能在错误的路径上传播,造成丢包率较高、时延较长的问题,提出了一种新的基于路径探索的贪婪路由算法。首先,以数据包传输时延为标准,运用人工蜂群算法对数字地图规划出的多条路由路径进行探索。其次,优化数据包在车辆之间的多跳转发方式。仿真结果表明,与贪婪周边无状态路由(GPSR)协议和最大持续时间最小角的GPSR(MM-GPSR)改进算法比较,在最好情况下,所提算法的数据包到达率分别提高了13.81%和9.64%,而该算法的数据包平均端到端时延分别降低了61.91%和27.28%。

Vehicular ad-hoc network greedy routing algorithm based on path exploration

In order to improve the transmission efficiency of information between vehicles in the city and realize the information sharing between vehicles, aiming at the problem that the current multi-hop unicast routing algorithm based on geographical location forwarding in the Vehicular Ad-hoc NETwork （VANET） does not consider the specificity of the urban scene and cannot adapt to the high dynamicity of vehicles in the city, so that the data packets between vehicles may spread on the wrong path, resulting in high packet loss rate and long delay, a new greedy routing algorithm based on path exploration was proposed. Firstly, taken the data packet transmission delay as the standard, artificial bee colony algorithm was used to explore multiple routing paths planned by the digital map. Then, the multi-hop forwarding method of data packets between vehicles was optimized. Simulation results show that, compared with Greedy Perimeter Stateless Routing (GPSR) protocol and Maxduration-Minangle GPSR (MM-GPSR) improved algorithm, in the best case, the data packet arrival rate of the proposed algorithm increases by 13.81% and 9.64% respectively, and the average data packet end-to-end delay of the proposed algorithm decreases by 61.91% and 27.28% respectively.