车联网建模和统计性质分析及其路由策略综述

doi:10.11772/j.issn.1001-9081.2015.12.3321

计算机应用 ›› 2015, Vol. 35 ›› Issue (12): 3321-3324.DOI: 10.11772/j.issn.1001-9081.2015.12.3321

• 网络与通信 • 下一篇

车联网建模和统计性质分析及其路由策略综述

陈宇峰¹, 向郑涛¹, 董亚波², 夏明³

1. 湖北汽车工业学院电气与信息工程学院, 湖北十堰 442002;
2. 浙江大学计算机科学与技术学院, 杭州 310027;
3. 浙江工业大学计算机科学与技术学院, 杭州 310023

收稿日期:2015-05-05 修回日期:2015-07-23 出版日期:2015-12-10 发布日期:2015-12-10
通讯作者: 向郑涛(1974-),男,湖北远安人,副教授,博士,CCF会员,主要研究方向:无线网络、智能交通
作者简介:陈宇峰(1973-),女,陕西户县人,教授,博士,CCF会员,主要研究方向:移动无线网络、复杂网络、网络性能分析;董亚波(1974-),男,浙江宁波人,副教授,博士,主要研究方向:移动网络、无线传感网络;夏明(1981-),男,山东泰安人,副教授,博士,主要研究方向:无线网络、无线传感器网络。
基金资助:
国家科技支撑计划项目(2014BAG01B02,2014BAG01B03);湖北省自然科学基金重点项目(2013CFA054);湖北省自然科学基金资助项目(2014CFB287);汽车动力传动与电子控制湖北省重点实验室(湖北汽车工业学院)开放基金资助项目(ZDK1201406);湖北汽车工业学院重大科研项目预研基金资助项目(2014XY02)。

Review of modeling, statistical properties analysis and routing strategies optimization in Internet of vehicles

CHEN Yufeng¹, XIANG Zhengtao¹, DONG Yabo², XIA Ming³

1. School of Electrical and Information Engineering, Hubei University of Automotive Technology, Shiyan Hubei 442002, China;
2. College of Computer Science and Technology, Zhejiang University, Hangzhou Zhejiang 310027, China;
3. College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou Zhejiang 310023, China

Received:2015-05-05 Revised:2015-07-23 Online:2015-12-10 Published:2015-12-10

摘要/Abstract

摘要： 利用复杂网络理论和方法对通信网络进行建模、分析网络演化过程中的统计性质,进而指导路由策略优化,已经成为热点领域。分析了车联网建模、车联网统计性质分析、车联网路由策略优化,以及车联网路由协议设计等方面的研究现状,并提出从三个方面进行改进,分别是:采用有向加权图来描述车联网的拓扑结构;从车联网与移动自组织网络的统计性质差异入手,寻找影响车联网传输能力的关键统计性质;利用复杂网络,研究基于多输入多输出技术的多径路由(即同时利用多个信道、多条路径传输)优化策略。

关键词: 车联网, 路由策略优化, 复杂网络, 车联网建模, 统计性质

Abstract: It has been a hot research area using the complex network theory and method to model the communication network, analyzing the statistical properties in evolving process and guiding the optimization of routing strategies. The research status of the modeling, the analysis of the statistical properties, the optimization of routing strategies and the design of routing protocols in the Internet of Vehicles (IoV) were analyzed. In addition, three improvements were proposed. The first is using the directed weighted graph to describe the topology of IoV. The second is analyzing the key statistical properties influencing the transmission capacity of IoV based on the differences of statistical properties between the IoV and the mobile Ad Hoc network. The third is optimizing the multi-path routing strategies based on Multiple-Input Multiple-Output (MIMO) technologies by the complex network, which means utilizing multiple channels and multiple paths to transmit.

Key words: Internet of Vehicles (IoV), routing strategies optimization, complex network, Internet of Vehicles (IoV) modeling, statistical property

中图分类号:

TP393

陈宇峰, 向郑涛, 董亚波, 夏明. 车联网建模和统计性质分析及其路由策略综述[J]. 计算机应用, 2015, 35(12): 3321-3324.

CHEN Yufeng, XIANG Zhengtao, DONG Yabo, XIA Ming. Review of modeling, statistical properties analysis and routing strategies optimization in Internet of vehicles[J]. Journal of Computer Applications, 2015, 35(12): 3321-3324.

参考文献

[1] YANG F, WANG S, LI J, et al. An overview of Internet of vehicles[J]. China Communications, 2014, 11(10):1-15.
[2] CHEN Z, WANG X. Effects of network structure and routing strategy on network capacity[J]. Physical Review E, 2006, 73(3):036107.
[3] ROS F J, MARTINEZ J A, RUIZ P M. A survey on modeling and simulation of vehicular networks:communications, mobility, and tools[J]. Computer Communications, 2014, 43(5):1-15.
[4] HO W H, LEUNG K K, POLAK J W. Stochastic model and connectivity dynamics for VANETs in signalized road systems[J]. IEEE/ACM Transactions on Networking, 2011, 19(1):195-208.
[5] THUAN D H, CUU H V, DO H N. VANET modelling and statistical properties of connectivity in urban environment[J]. REV Journal on Electronics and Communications, 2013, 3(1/2):50-58.
[6] NABOULSI D, FIORE M. On the instantaneous topology of a large-scale urban vehicular network:the cologne case[C]//MobiHoc:Proceedings of the 14th ACM International Symposium on Mobile Ad Hoc Networking and Computing. New York:ACM, 2013:167-176.
[7] GRZYBEK A, DANOY G, SEREDYNSKI M, et al. Evaluation of dynamic communities in large-scale vehicular networks[C]//DIVANet:Proceedings of the 3rd ACM International Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications. New York:ACM, 2013:93-100.
[8] PALLIS G, KATSAROS D, DIKAIAKOS M D, et al. On the structure and evolution of vehicular networks[C]//MASCOTS:Proceedings of the 17th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems. Piscataway:IEEE, 2009:502-511.
[9] CONCEICO H, FERREIRA M, BARROS J. On the urban connectivity of vehicular sensor networks[C]//DCOSS:Proceedings of the 4th IEEE International Conference on Distributed Computing in Sensor Systems, LNCS 5067. Berlin:Springer, 2008:112-125.
[10] ZHANG L, CHEN H, LI C, et al. Modeling the vehicular Ad Hoc networks based on topology characteristics in urban scenario[J]. Journal of software, 2013, 24(1):51-61. (张丽丽,陈浩,李臣明,等.城市环境下基于拓扑特性的车辆自组网建模[J].软件学报,2013,24(1):51-61.)
[11] ZHANG H, LI J, LYU Y. Structure performance analysis of vehicular Ad Hoc networks based on complex network theory[J]. Computer Modelling and New Technologies, 2014, 18(2):46-51.
[12] COSTA L D F, RODRIGUES F A, TRAVIESO G, et al. Characterization of complex networks:a survey of measurements[J]. Advances in Physics, 2007, 56(1):167-242.
[13] TONG C, NIU J, QU G, et al. Complex networks properties analysis for mobile Ad Hoc networks[J]. IET Communications, 2012, 6(4):370-380.
[14] WANG Y, MA Y, WANG Y, et al. Evolving network model with local-area preference for mobile Ad Hoc network[J]. China Communications, 2013, 10(5):146-155.
[15] SHAREF B T, ALSAQOUR R A, ISMAIL M. Vehicular communication Ad Hoc routing protocols:a survey[J]. Journal of Network and Computer Applications, 2014, 40(2):363-396.
[16] RAVITEJA B L, ANNAPPA B, TAHILIANI M P. CAMP:congestion adaptive multipath routing protocol for VANETs[C]//ADCONS'11:Proceedings of the 2011 International Conference on Advanced Computing, Networking and Security, LNCS 7135. Berlin:Springer, 2012:318-327.
[17] JAYAVEL J, VENKATESAN R, VINOTH D. Efficient multipath routing protocol for VANET using path restoration[J]. International Journal of Engineering and Technology, 2013, 5(5):3839-3845.
[18] CHEN Z, GUAN L, WANG X, et al. Ad-Hoc on-demand multipath distance vector routing with backup route update mechanism[C]//HPCC & ICESS:Proceedings of the 14th IEEE International Conference on High Performance Computing and Communications and the 9th IEEE International Conference on Embedded Software and Systems. Piscataway:IEEE, 2012:908-913.
[19] CHEN Y, XIANG Z, JIAN W, et al. A cross-layer AOMDV routing protocol for V2V communication in urban VANET[C]//Proceedings of the 5th International Conference on Mobile Ad-Hoc and Sensor Networks. Piscataway:IEEE, 2009:353-359.
[20] CHEN Y, XIANG Z, JIAN W, et al. An adaptive cross-layer multi-path routing protocol for urban VANET[C]//Proceedings of the 2010 IEEE International Conference on Automation and Logistics. Piscataway:IEEE, 2010:603-608.
[21] ZHAO L, LAI Y-C, PARK K, et al. Onset of traffic congestion in complex networks[J]. Physical Review E, 2005, 71(2):026125.
[22] ZHAO L, CUPERTINO T H, PARK K, et al. Optimal structure of complex networks for minimizing traffic congestion[J]. Chaos, 2007, 17(4):043103.
[23] GUO D, LIANG M, WANG Z, et al. Network capacity based on complex network theory[J]. Journal of Beijing Jiaotong University, 2011, 35(3):123-127, 131. (郭东超,梁满贵,王哲,等.基于复杂网络理论的网络容量估算[J].北京交通大学学报,2011,35(3):123-127,131.)
[24] LI S, LOU L, CHEN R, et al. A pervasive optimized algorithm for complex network routing strategy[J]. Acta Physica Sinica, 2014, 63(2):028901. (李世宝,娄琳琳,陈瑞祥,等.一种复杂网络路由策略的普适优化算法[J].物理学报,2014,63(2):028901.)
[25] YANG H, WANG W, XIE Y, et al. Transportation dynamics on networks of mobile Agents[J]. Physical Review E, 2011, 83(1):016102.
[26] BRUST M R, TURGUT D, RIBEIRO C H C, et al. Is the clustering coefficient a measure for fault tolerance in wireless sensor networks?[C]//Proceedings of the 2012 IEEE International Conference on Communications. Piscataway:IEEE, 2012:183-187.
[27] CHEN S, HUANG W, CATTANI C, et al. Traffic dynamics on complex networks:a survey[J]. Mathematical Problems in Engineering, 2012, 2012(1):256-267.
[28] SCHLEICH J, DANOY G, DORRONSORO B, et al. An overlay approach for optimising small-world properties in VANETs[C]//Proceedings of the 16th European Conference on Applications of Evolutionary Computation, LNCS 7835. Berlin:Springer, 2013:32-41.
[29] LU N, ZHANG N, CHENG N, et al. Vehicles meet infrastructure:towards capacity-cost tradeoffs for vehicular access networks[J]. IEEE Transactions on Intelligent Transportation Systems, 2013, 14(3):1266-1277.
[30] NEKOUI M, PISHRO-NIK H. Throughput scaling laws for vehicular Ad Hoc networks[J]. IEEE Transactions on Wireless Communications, 2012, 11(8):2895-2905.
[31] KAI C H, LONG J, LING X, et al. Upper bound of network capacity and a static optimal packet routing strategy[J]. Physica A:Statistical Mechanics and its Applications, 2014, 401(5):174-181.
[32] EIZA M H, NI Q. An evolving graph-based reliable routing scheme for VANETs[J]. IEEE Transactions on Vehicular Technology, 2013, 62(4):1493-1504.
[33] MAO G Q, ANDERSON B D O. Graph theoretic models and tools for the analysis of dynamic wireless multihop networks[C]//WCNC:Proceedings of the 2009 IEEE Wireless Communications and Networking Conference. Piscataway:IEEE, 2009:1-6.
[34] GUAN X, ZHANG X, ZHU Y, et al. An efficient routing strategy on spatial scale-free networks[J]. International Journal of Modern Physics C, 2014, 25(7):809-820.
[35] ZHANG H, LI J. Topological characteristics and control approach for VANET[J]. Journal of Transportation Systems Engineering and Information Technology, 2015, 15(2):81-87. (张宏,李杰.车载自组织网络拓扑特性及控制[J].交通运输系统工程与信息,2015,15(2):81-87.)
[36] SHIVSHANKAR S, JAMALIPOUR A. An evolutionary game theory-based approach to cooperation in VANETs under different network conditions[J]. IEEE Transactions on Vehicular Technology, 2015, 64(5):2015-2022.
[37] JUNG E S, VAIDYA N H. A power control MAC protocol for Ad Hoc networks[J]. Wireless Networks, 2005, 11(1/2):55-66.
[38] LU N, SHEN X. Scaling laws for throughput capacity and delay in wireless networks-a survey[J]. IEEE Communications Surveys and Tutorials, 2014, 16(2):642-657.

车联网建模和统计性质分析及其路由策略综述

Review of modeling, statistical properties analysis and routing strategies optimization in Internet of vehicles

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