车载自组网信息交互最大流传输优化策略

doi:10.3969/j.issn.1000-3428.2017.05.002

计算机工程

所属专题：智能交通专题；

车载自组网信息交互最大流传输优化策略

谭大禹^1a,李敬兆 ^1a,1b,杨大禹^1a,1b,李子豪²,杨高明 ^1a

(1.安徽理工大学 a.计算机科学与工程学院; b.电气与信息工程学院,安徽淮南 232001; 2.复旦大学信息科学与工程学院,上海 200433)

收稿日期:2016-08-10 出版日期:2017-05-15 发布日期:2017-05-15
作者简介:谭大禹(1991—),男,硕士研究生,主研方向为物联网、无线传感网、分布式计算;李敬兆(通信作者),教授、博士、博士生导师;杨大禹,博士;李子豪,硕士研究生;杨高明,副教授、博士。
基金资助:
国家自然科学基金(61170060);安徽省学术与技术带头人学术科研活动资助项目(2015D046);安徽省高等学校优秀拔尖人才项目(gxbjZD2016044)。

Optimization Strategy of Information Interaction Maximum Flow Transmission in Vehicle Ad Hoc Network

TAN Dayu ^1a,LI Jingzhao ^1a,1b,YANG Dayu ^1a,1b,LI Zihao ²,YANG Gaoming ^1a

(1a.School of Computer Science and Engineering; 1b.School of Electrical and Information Engineering, Anhui University of Science and Technology,Huainan,Anhui 232001,China; 2.School of Information Science and Technology,Fudan University,Shanghai,200433,China)

Received:2016-08-10 Online:2017-05-15 Published:2017-05-15

摘要/Abstract

摘要： 在智能车联网中,多用户请求大量数据资源时存在传输不稳定的问题。为此,在车辆节点移动环境下提出集合覆盖最大流(SCMF)算法。利用集合覆盖方法考虑更多请求细节并分析最优化随机需求模型,优化信息资源共享和数据传输过程,保证车辆与无线访问节点及车辆之间信息交互以最大流效率传输,快速稳定地处理客户大数据资源请求。实验结果表明,SCMF算法能够以较少的网络开销和传输延时获得较高的传输效率,提高网络资源利用率和综合性能。

关键词: 车载自组网, 集合覆盖, 资源分配, 集合覆盖最大流, 高效传输

Abstract: Aiming at the transmission instability problem when multiple users request a large number of data resources in intelligent vehicle network,this paper proposes a Set Covering Maximum Flow(SCMF) algorithm in mobile vehicle node environment.It uses set covering method to consider more request details and analyzes optimal stochastic demand model,which optimizes information resource sharing and data transmission process,guarantees vehicle information interaction between vehicle and wireless Access Point(AP) nodes with maximum flow efficiency transmission,and processes the customer’s big data resource request quickly and steadily.Experimental results show that the SCMF algorithm can obtain higher transmission efficiency with lower network overhead and transmission delay.It improves the utilization of network resources and comprehensive performance.

Key words: Vehicle Ad Hoc Network(VANET), set covering, resource allocation, Set Covering Maximum Flow(SCMF), efficient transmission

中图分类号:

TP319

谭大禹,李敬兆,杨大禹,李子豪,杨高明. 车载自组网信息交互最大流传输优化策略[J]. 计算机工程, doi: 10.3969/j.issn.1000-3428.2017.05.002.

TAN Dayu,LI Jingzhao,YANG Dayu,LI Zihao,YANG Gaoming. Optimization Strategy of Information Interaction Maximum Flow Transmission in Vehicle Ad Hoc Network[J]. Computer Engineering, doi: 10.3969/j.issn.1000-3428.2017.05.002.

http://www.ecice06.com/CN/Y2017/V43/I5/8

参考文献

参考文献［1］Sichitiu M L,Kihl M.Inter-vehicle Communication Systems:A Survey［J］.IEEE Communications Surveys & Tutorials,2008,10(2):88-105. ［2］Zhao Jing,Cao Guohong.VADD:Vehicle-assisted Data Delivery in Vehicular Ad Hoc Networks［J］.IEEE Transactions on Vehicular Technology,2008,57(3):1910-1922. ［3］Tom H L,Shen X M,Bai Fan.Integrity-oriented Content Transmission in Highway Vehicular Ad Hoc Network［C］//Proceedings of IEEE INFCOM’13.Washington D.C.,USA:IEEE Press,2013:2562-2570. ［4］Song Chao,Liu Ming,Gong Haigang,et al.Distributed Real-time Information Based Routing Protocol in Vehicular Ad-hoc Networks［J］.Journal of Software,2011,22(3):466-480. ［5］Belt J,Ahmadi H,Doyle L E,et al.A Dynamic Embedding Algorithm for Wireless Network Virtualization［C］//Proceedings of the 80th IEEE Vehicular Technology Conference.Washington D.C.,USA:IEEE Press,2014:1-6. ［6］Guo Bingyi,Guan Quansheng,Yu F R,et al.Energy-efficient Topology Control with Selective Diversity in Cooperative Wireless Ad Hoc Networks:A Game-therotic Approach［J］.IEEE Transactions on Wireless Communications,2014,13(11):6484-6495. ［7］Shang Dezhong,Zhang Baoxian,Yao Zheng,et al.An Energy Efficient Localized Topolopy Control Algorithm for Wireless Multi-hop Networks［J］.IEEE Journal of Communications and Networks,2014,16(4):371-377. ［8］Zhang Xinming,Zhang Yue,Yan Fan,et al.Interference-based Topology Control Algorithm for Delay-constrained Mobile Ad Hoc Networks ［J］.IEEE Transactions on Mobile Computing,2015,14(4):742-754. ［9］Eslamlu G,Sabaei M,Fereydooni M.Delay-constraint Load-aware Topology Control in Wireless Sensor Networks［C］//Proceedings of the 35th International Conference on Telecom-munications and Signal Processing.Washington D.C.,USA:IEEE Press,2012:27-31. ［10］Li Deying,Wang Baobing,Jia Xiaohua.Topology Control for Throughput Out Optimization in Wireless Mesh Networks［C］//Proceedings of International Conference on Mobile Ad-hoc and Sensor Networks.Hongkong,China:［s.n.］,2008:161-168. ［11］Tao Wenhui,Chen Cailian,Yang Bo,et al.Adaptive Topology Control for Throughput Optimization in Wireless Sensor Networks［C］//Proceedings of the 12th IEEE International Conference on Communication Technology.Washington D.C.,USA:IEEE Press,2010:1299-1302. ［12］Muhammed A V K,Neelakantan P C,Babu A V.Network Connectivity of One-dimensional Networks Vehicular Ad Hoc Network［C］//Proceedings of IEEE 2011 International Conference on Communications and Signal Processing.Calicut,India:［s.n.］:2011:241-245. ［13］Keykaie S,Mahoudifar A.Study of Connectivity in a Vehicular Ad Hoc Network with Random Node Speed Distribution［C］//Proceedings of the 6th International Conference on New Technologies,Mobility and Security.Dubai,Saudi Arabia:［s.n.］,2014:1-4. ［14］Wang Yu,Wu Hongyi.Delay/Fault-tolerant Mobile Sensor Network(DFT-MSN):A New Paradigm for Pervasive Information Gathering［J］.IEEE Transactions on Mobile Computing,2006,6(8):1021-1034. ［15］Wu C,Kumekawa K,Kato T.Distributed Reinforcement Learning Approach for Vehicular Ad Hoc Networks［J］.IEICE Transactions on Communications,2010,93-B(6):1431-1442. (下转第22页) (上接第15页) ［16］朱金奇,马春梅,刘明,等.车载自组织网络中基于停车骨干网络的数据传输［J］.软件学报,2016,27(2):432-450. ［17］刘冰艺,吴黎兵,贾东耀,等.基于移动云服务的车联网数据上传策略［J］.计算机研究与发展,2016,53(4):811-823. ［18］冯成,李志军,姜守旭,等.无线移动感知网络上的数据聚集传输规划［J］.计算机学报,2015,38(3):685-700. ［19］You Kun,Tang Bin,Qian Zhuzhong,et al.QoS-aware Placement of Stream Processing Service［J］.Journal of Supercomputing,2013,64(3):919-941. ［20］Rochman Y,Levy H,Brosh E.Resource Placement and Assignment in Distributed Network Topologies［C］//Proceedings of IEEE INFOCOM’13.Washington D.C.,USA:IEEE Press,2013:1914-1922. ［21］Rochman Y,Levy H,Brosh E.Efficient Resource Placement in Cloud Computing and Network Applications［J］.ACM SIGMETRICS Performance Evaluation Review,2014,42(2):49-51. 编辑金胡考

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