计算机应用 ›› 2019, Vol. 39 ›› Issue (2): 518-522.DOI: 10.11772/j.issn.1001-9081.2018061256

• 计算机软件技术 • 上一篇    下一篇

车联网环境下基于节点认知交互的路由算法

樊娜1, 朱光源1, 康军1, 唐蕾1, 朱依水1, 王路阳1, 段嘉欣2   

  1. 1. 长安大学 信息工程学院, 西安 710064;
    2. 陕西城际铁路有限公司, 西安 710018
  • 收稿日期:2018-06-19 修回日期:2018-08-20 出版日期:2019-02-10 发布日期:2019-02-15
  • 通讯作者: 朱光源
  • 作者简介:樊娜(1978-),女,陕西渭南人,副教授,博士,CCF会员,主要研究方向:无线传感器、网络安全;朱光源(1994-),男,江苏镇江人,硕士研究生,主要研究方向:交通信息控制;康军(1975-),男,陕西西安人,副教授,博士,主要研究方向:大数据、智能交通系统;唐蕾(1984-),女,四川江油人,副教授,博士,主要研究方向:交通信息服务计算;朱依水(1981-),女,陕西宝鸡人,讲师,博士,主要研究方向:服务计算、交通信息服务;王路阳(1988-),男,陕西西安人,讲师,博士,主要研究方向:交通信息服务;段嘉欣(1985-),女,陕西宝鸡人,主要研究方向:交通信息服务。
  • 基金资助:
    陕西省留学回国人员科技活动择优资助项目(2017023);陕西省重点创新团队项目(2017KCT-29);陕西省重点研发项目(2018GY-032);中央高校基本科研业务费资助项目(310824171007)。

Routing algorithm based on node cognitive interaction in Internet of vehicles environment

FAN Na1, ZHU Guangyuan1, KANG Jun1, TANG Lei1, ZHU Yishui1, WANG Luyang1, DUAN Jiaxin2   

  1. 1. School of Information Engineering, Chang'an University, Xi'an Shaanxi 710064, China;
    2. Shaanxi Intercity Railway Company Limited, Xi'an Shaanxi 710018, China
  • Received:2018-06-19 Revised:2018-08-20 Online:2019-02-10 Published:2019-02-15
  • Supported by:
    This work is partially supported by the Selected Science and Technology Project of Oversea Scholars from Shaanxi Province (2017023), the Key Innovation Team Project of Shaanxi Province (2017KCT-29), the Key Research and Development Project of Shaanxi Province (2018GY-032), the Fundamental Research Funds for the Central Universities (310824171007).

摘要: 针对车联网(IoV)环境下消息传输效率低下、网络资源开销较大等诸多问题,提出一种适用于城市交通场景下基于车辆节点认知交互的路由算法。首先,依据信任理论提出节点认知交互度的概念,并在此基础上对车联网中的车辆节点进行分类,赋予它们不同的认知交互度初值;同时还引入车辆节点交互时间、交互频率、车辆节点物理间隔距离、间隔跳数以及消息生存时间等影响因子,进而构建了车辆节点认知交互评估模型。基于该模型计算并更新节点的认知交互度,并通过比较对应车辆节点间的认知交互度值来选取认知交互度相对较高的邻居节点作为中继节点进行消息转发。仿真实验结果表明,与Epidemic和Prophet路由算法相比,所提路由算法有效提高了消息投递率并降低了消息投递时延,同时显著降低了网络资源的开销,有助于提升车联网环境的消息传输质量。

关键词: 车联网, 延迟容忍网络, 路由算法, 消息转发

Abstract: In order to solve the problems such as low transmission efficiency and high network resource overhead in Internet of Vehicles (IoV) environment, a new routing algorithm based on node cognitive interaction, which is suitable for urban traffic environment, was proposed. Firstly, based on trust theory, a concept of cognitive interaction degree was proposed. Then, based on this, the vehicle nodes in IoV were classified and given with different initial values of cognitive interaction degree. Meanwhile, the influence factors such as interaction time, interaction frequency, physical distance, hops between nodes and the Time-To-Live of message were introduced, and a cognitive interaction evaluation model of vehicle nodes was constructed. The cognitive interaction degrees of vehicle nodes were calculated and updated by using the proposed model, and a neighbor node with higher cognitive interaction degree than others could be selected as relay node to forward the messages after the comparison between the nodes. Simulation results show that compared with Epidemic and Prophet routing algorithms, the proposed algorithm effectively increases the message delivery rate and reduces the message delivery delay, while significantly reducing the overhead of network resources and helping to improve the quality of message transmission in IoV environment

Key words: Internet of Vehicles (IoV), Delay Tolerant Network (DTN), routing algorithm, message forwarding

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