软件定义车联网的数据转发策略和路由选择技术

doi:10.11772/j.issn.1001-9081.2017071969

计算机应用 ›› 2018, Vol. 38 ›› Issue (1): 26-30.DOI: 10.11772/j.issn.1001-9081.2017071969

• 2017年全国开放式分布与并行计算学术年会(DPCS 2017)论文 • 上一篇下一篇

软件定义车联网的数据转发策略和路由选择技术

董柏宏, 邓健, 张定杰, 吴维刚

中山大学数据科学与计算机学院, 广州 510006

收稿日期:2017-08-11 修回日期:2017-09-08 出版日期:2018-01-10 发布日期:2018-01-22
通讯作者: 吴维刚
作者简介:董柏宏(1993-),男,广东茂名人,硕士研究生,主要研究方向:车联网;邓健(1993-),男,广东茂名人,硕士研究生,主要研究方向:车联网、命名数据网络;张定杰(1992-),男,广东梅州人,硕士,主要研究方向:车联网;吴维刚(1976-),男,山东泰安人,教授,博士,主要研究方向:车联网、云计算。
基金资助:
国家自然科学基金资助项目（61379157）；广东省科技计划项目（2015B010111001）。

Technology on data forwarding and routing selection for software defined vehicular Ad Hoc network

DONG Baihong, DENG Jian, ZHANG Dingjie, WU Weigang

School of Data and Computer Science, Sun Yat-Sen University, Guangzhou Guangdong 510006, China

Received:2017-08-11 Revised:2017-09-08 Online:2018-01-10 Published:2018-01-22
Supported by:
This work is partially supported by the National Natural Science Foundation of China (6137915), the Science and Technology Planning Project of Guangdong Province (2015B010111001).

摘要/Abstract

摘要： 针对目前车联网（VANET）数据转发效率低的问题，提出了软件定义网络（SDN）的数据转发策略和路由选择技术。首先，采用了软件定义车联网的分层控制结构，由局部控制器和全局控制器组成，实现数据转发和控制分离，可灵活控制数据转发的方向；然后，设计了单条路段的车辆路由机制，该机制预测车辆节点位置并采用贪心策略，实现数据的稳定传输；其次，设计了多个需求间的路段路由机制，该机制采用广度优先搜索（BFS）算法和边集相结合的方式，实现多个需求间路径不相交，缓解带宽瓶颈问题；最后，通过仿真验证，对比无线自组网按需平面距离向量（AODV）路由，所提出的数据转发策略和路由选择算法在数据分组接收率上提高40%以上，平均延迟时间降低60%左右。实验结果表明，软件定义车联网的数据转发策略和路由选择技术能够提高数据转发效率，减少平均收包延时。

关键词: 软件定义网络, 车联网, 数据路由, 路径不相交, 贪心策略

Abstract: Since the data forwarding in Vehicular Ad Hoc Network (VANET) is inefficient, a technology on data forwarding and routing selection based on Software Defined Network (SDN) was proposed. Firstly, a hierarchical architecture of SDN based VANET, which was consist of local controller and global controller, was used to separate data forwarding from transmission control and decide the direction of data forwarding flexibly. Secondly, a vehicular routing mechanism of single road section was designed and data could be transmitted stably by predicting vehicular position and using greedy strategy. Thirdly, to achieve the goal of path disjoint which could avoid the bandwidth bottleneck between multiple demands, a road section routing mechanism was proposed, which combined the Breadth First Search (BFS) and edge set. Finally, compared with Ad Hoc On-demand Distance Vector (AODV) routing, the proposed algorithm could increase data reception rate by 40% and reduce average delay by 60%. The simulation results show that the technology on data forwarding and routing for software defined VANET can effectively improve the data delivery rate, and reduces the average packet delay.

Key words: Software Defined Network (SDN), Vehicular Ad Hoc Network (VANET), data routing, path disjoint, greedy strategy

中图分类号:

TP311
TP393

董柏宏, 邓健, 张定杰, 吴维刚. 软件定义车联网的数据转发策略和路由选择技术[J]. 计算机应用, 2018, 38(1): 26-30.

DONG Baihong, DENG Jian, ZHANG Dingjie, WU Weigang. Technology on data forwarding and routing selection for software defined vehicular Ad Hoc network[J]. Journal of Computer Applications, 2018, 38(1): 26-30.

参考文献

[1] 马静.车联网的关键技术及其应用研究[J].江苏科技信息,2016(24):50-52.(MA J. Key technology and application research of the Internet of vehicles[J]. Jiangsu Science & Technology Information, 2016(24):50-52.)
[2] TOOR Y, MUHLETHALER P, LAOUITI A, et al. Vehicle Ad Hoc networks:applications and related technical issues[J]. IEEE Communications Surveys and Tutorials, 2008, 10(3):74-88.
[3] KAUR M. Vehicular Ad Hoc networks[J]. Journal of Global Research in Computer Science, 2012, 3(3):61-64.
[4] 章学宇.车载自组织网络路由协议研究[D].长沙:湖南大学,2010:18-34.(ZHANG X Y. The research on routing protocols in vehicular Ad Hoc networks[D]. Changsha:Hunan University, 2010:18-34.)
[5] JAAP S, BECHLER M, WOLF L. Evaluation of routing protocols for vehicular Ad Hoc networks in typical road traffic scenarios[C]//Proceedings of the 11th EUNICE Open European Summer School on Networked Applications. Madrid:[s.n.], 2005:584-602.
[6] GOONEWARDENE R T, ALI F H, STIPIDIS E. Robust mobility adaptive clustering scheme with support for geographic routing for vehicular Ad Hoc networks[J]. IET Intelligent Transport Systems, 2009, 3(2):148-158.
[7] KRCO S, DUPCINOV M. Improved neighbor detection algorithm for AODV routing protocol[J]. IEEE Communications Letters, 2003, 7(12):584-586.
[8] ASWATHY M C, TRIPTI C. A cluster based enhancement to AODV for inter-vehicular communication in VANET[J]. International Journal of Grid Computing & Applications, 2012, 3(3):41-50.
[9] THOMAS N D, GRAY K. SDN:Software Defined Networks[M]. Sebastopol:O'Reilly Media, 2014, 8(7):31-38.
[10] KU I, LU Y, GERLA M, et al. Towards software-defined VANET:architecture and services[C]//Proceedings of the 201413th Annual Mediterranean Ad Hoc Networking Workshop. Piscataway, NJ:IEEE, 2014:103-110.
[11] SHIN M K, NAM K H, KIM H J. Software-Defined Networking (SDN):a reference architecture and open APIs[C]//ICTC 2012:Proceedings of the 2012 International Conference on ICT Convergence. Piscataway, NJ:IEEE, 2012:360-361.
[12] LI H, DONG M, OTA K. Control plane optimization in software-defined vehicular Ad Hoc networks[J]. IEEE Transactions on Vehicular Technology, 2016, 65(10):7895-7904.
[13] TRUONG N B, LEE G M, GHAMRI-DOUDANE Y. Software defined networking-based vehicular Ad Hoc network with fog computing[C]//Proceedings of the 2015 IFIP/IEEE International Symposium on Integrated Network Management. Piscataway, NJ:IEEE, 2015:1202-1207.
[14] 崔翠梅,杨德智,姜程鑫.基于NS3的移动认知网络仿真系统[J].通信技术,2016,49(11):1509-1513.(CUI C M, YANG D Z, JIANG C X. NS3-based Simulation System for Mobile Cognitive Radio Networks[J]. Communications Technology, 2016, 49(11):1509-1513.)

[1]	陈成瑞, 孙宁, 何世彪, 廖勇. 面向C-V2X通信的基于深度学习的联合信道估计与均衡算法[J]. 计算机应用, 2021, 41(9): 2687-2693.
[2]	陈葳葳, 曹利, 顾翔. 基于区块链的车联网电子取证模型[J]. 计算机应用, 2021, 41(7): 1989-1995.
[3]	王家瑞, 谭国平, 周思源. 高速车联网场景下分簇式无线联邦学习算法[J]. 计算机应用, 2021, 41(6): 1546-1550.
[4]	许红亮, 杨桂芹, 蒋占军. 基于软件定义网络的数据中心自适应多路径负载均衡算法[J]. 计算机应用, 2021, 41(4): 1160-1164.
[5]	陈港, 孟相如, 康巧燕, 阳勇. 基于拓扑分割与聚类分析的虚拟软件定义网络映射算法[J]. 《计算机应用》唯一官方网站, 2021, 41(11): 3309-3318.
[6]	巫光福, 王影军. 基于区块链与云-边缘计算混合架构的车联网数据安全存储与共享方案[J]. 计算机应用, 2021, 41(10): 2885-2892.
[7]	陈锦宇, 刘兆伟. 基于改进投票证明共识协议的车联网系统[J]. 计算机应用, 2021, 41(1): 170-176.
[8]	汤星峰, 徐卿钦, 马世纬. 基于路径探索的车载自组网贪婪路由算法[J]. 计算机应用, 2020, 40(6): 1738-1744.
[9]	韩雨涝, 房鼎益. 联合无线充电与数据收集的移动充电装置多目标路径规划算法[J]. 计算机应用, 2020, 40(6): 1745-1750.
[10]	朱梦迪, 束永安. 软件定义网络中控制数据平面一致性的验证[J]. 计算机应用, 2020, 40(6): 1751-1754.
[11]	黄辰, 曹建农, 王时绘, 张龑. 基于协作反馈控制算法的车联网行车安全动态强化模型[J]. 计算机应用, 2020, 40(4): 1209-1214.
[12]	向雄, 田检. 基于软件定义网络的对等网传输调度优化[J]. 计算机应用, 2020, 40(3): 777-782.
[13]	赵季红, 吴豆豆, 曲桦, 殷振宇. 基于软件定义网络的可靠性虚拟网络映射保障机制[J]. 计算机应用, 2020, 40(3): 770-776.
[14]	陈葳葳, 曹利, 邵长虹. 基于区块链技术的车联网高效匿名认证方案[J]. 计算机应用, 2020, 40(10): 2992-2999.
[15]	池亚平, 莫崇维, 杨垠坦, 陈纯霞. 面向软件定义网络架构的入侵检测模型设计与实现[J]. 计算机应用, 2020, 40(1): 116-122.

软件定义车联网的数据转发策略和路由选择技术

Technology on data forwarding and routing selection for software defined vehicular Ad Hoc network

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics