基于路径时延模型的车联网数据分发方案

针对车联网的容迟特性造成通信资源受限的问题，提出了满足副本抑制要求的数据分发方案.方案利用马尔可夫链，通过交通网络的车辆概率分布建立路段的期望传输时延，并结合车辆的轨迹与目标位置的匹配度确定车辆的转发优先级.车辆为转发的每个数据包插入转发参数字段并通过同步反馈机制确定最终的转发车辆，确保由优先级最高的车辆完成转发.考虑到链路的稳定性，还推导了当前丢包率前提下，车辆接收数据包与发送次数之比，避免不必要的发送尝试产生大量副本.实验结果显示，提出的方案与基于轨迹预测的算法相比，有效提高了网络吞吐量和时延性能.

Data Dissemination Based on Road Delay for VANETs

Considering that the delay tolerant character of VANETs (Vehicular Ad hoc NETworks),a packet dissemination strategy is introduced for duplicate controlling in VANETs of urban area.A packet transmission delay model of road is constructed based on Markov chain and vehicles distribution.The delay model is used to build the expected transmission delay of vehicles.And then the priority of vehicles is determined by the expected transmission delay and destination position.Current data carder inserts decision segment of candidates into packets and select next hop vehicle by acknowledgement.Therefore,it is guaranteed that the vehicle with the highest priority can be selected as the next carrier.Furthermore,the paper deduces the ratio of quantities of received and transmitted packets.The ratio can be used to limit the unnecessary transmitting attempt,so as to inhibit duplicate packets.Simulation results demonstrate that the strategy achieves higher throughput and delay performance than the trajectory prediction based algorithms by limiting duplicate packets.