基于路径时延模型的车联网数据分发方案

发布时间：2018-06-15 16:59

本文选题：车联网 + 数据副本　；参考：《电子学报》2017年09期

【摘要】：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.
[Abstract]:Aiming at the problem of limited communication resources caused by the delay tolerance of vehicle networking, a data distribution scheme to meet the requirement of replica suppression is proposed. Using Markov chain, the expected transmission delay is established by the vehicle probability distribution of the traffic network, and the vehicle forwarding priority is determined by the matching degree between the vehicle trajectory and the target position. The vehicle inserts the forwarding parameter field for each packet forwarded and determines the final forwarding vehicle by synchronous feedback mechanism to ensure that the vehicle with the highest priority is forwarded. Considering the stability of the link, the ratio of the received data packet to the number of times of transmission is deduced under the premise of the current packet loss rate, so as to avoid unnecessary transmission attempts to produce a large number of replicas. Experimental results show that the proposed scheme improves the throughput and delay performance of the network effectively compared with the algorithm based on trajectory prediction.
【作者单位】：湖南理工学院信息与通信工程学院复杂工业物流系统智能控制与优化湖南省重点实验室;湖南大学嵌入式与网络计算湖南省重点实验室;
【基金】：国家自然科学基金(No.61300039) 中国博士后基金面上项目(No.2013M542109) 湖南省自然科学基金(No.14JJ3130) 湖南省教育厅重点项目(No.12A057) 湖南省科技计划项目(No.2016TP1021) 湖南省高校创新平台开放基金项目(No.16K037)
【分类号】：TN929.5;U495

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