基于无标度网络的车联网连通性研究

doi:10.11959/j.issn.1000-436x.2021101

通信学报 ›› 2021, Vol. 42 ›› Issue (4): 100-108.doi: 10.11959/j.issn.1000-436x.2021101

• 专题：面向未来移动网络的大规模组网关键技术 • 上一篇下一篇

基于无标度网络的车联网连通性研究

韩涛¹, 贺威¹, 代俊¹, 左勇², 杨旸³^,⁴, 葛晓虎¹

¹ 华中科技大学电子信息与通信学院，湖北武汉 430074
² 国防科技大学电子科学学院，湖南长沙 410003
³ 上海科技大学信息科学与技术学院，上海 201210
⁴ 鹏城实验室网络通信研究中心，广东深圳 518000

修回日期:2021-04-12 出版日期:2021-04-25 发布日期:2021-04-01
作者简介:韩涛（1970- ），男，湖北武汉人，博士，华中科技大学教授，主要研究方向为移动通信、多媒体通信、计算机网络、车联网等。
贺威（1992- ），男，湖北武汉人，华中科技大学博士生，主要研究方向为无线通信、车联网、复杂网络、无线传感器网络等。
代俊（1995- ），女，湖北襄樊人，华中科技大学硕士生，主要研究方向为车联网、大偏差、移动通信、人工智能等。
左勇（1983- ），男，湖南长沙人，博士，国防科技大学副教授，主要研究方向为卫星通信、物联网、导航与通信融合技术。
杨旸（1974- ），男，江苏东台人，博士，上海科技大学教授，主要研究方向为 5G/6G 移动通信网络、物联网、多层次算力网络、开放无线测试验证平台等。
葛晓虎（1972- ），男，湖北武汉人，博士，华中科技大学教授，主要研究方向为移动通信、无线网络中的流量建模、绿色通信等。
基金资助:
国家自然科学基金资助项目(62071190)

Connectivity analysis of IoV based on scale-free network

Tao HAN¹, Wei HE¹, Jun DAI¹, Yong ZUO², Yang YANG³^,⁴, Xiaohu GE¹

¹ School of Electronic Information and Communication, Huazhong University of Science and Technology, Wuhan 430074, China
² School of Electronic Science, National University of Defense Technology, Changsha 410003, China
³ School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China
⁴ Research Center for Network Communication, Peng Cheng Laboratory, Shenzhen 518000, China

Revised:2021-04-12 Online:2021-04-25 Published:2021-04-01
Supported by:
The National Natural Science Foundation of China(62071190)

摘要/Abstract

摘要：

移动车辆的连通性是车联网（IoV）的关键指标之一，它会严重影响数据传输的性能。由于车联网的网络拓扑高频动态变化，车辆之间的通信链路容易频繁地断连。如何降低链路建立的随机性和链路断开概率，提高整体网络的连通性一直是急需解决的关键问题。针对上述问题，在视距路径损耗模型和干扰模型下分析网络的连通性，通过对车联网链路在真实世界的表征，设计动态生长（DN）算法。对车辆节点进行增加、删除和链路的偏好连接后，构建无标度车联网。通过仿真结果分析，网络整体的连通性提升了16%。

关键词: 车联网, 连通性, 节点度分布, 复杂网络, 无标度车联网

Abstract:

The connectivity of moving vehicles is one of the critical metrics in Internet of vehicles (IoV) that critically influence the performance of data transmission.Due to the high-frequency dynamic changes of the network topology of the IoV, which causes the link to be easily disconnected frequently.It is a critical issue to reduce the probability of link disconnection, and reducing the randomness of link establishment improves the overall network connectivity.To solve the above problems, the network’s connectivity was analyzed under the line of sight path loss model and the interference model, and the dynamic growth (DN) algorithm was designed through the characterization of the IoV link in the real world.Moreover, a scale-free VANET was built through the network’s addition and deletion of nodes and link preference connections.Simulation results indicate that the overall connectivity of the network is improved by 16%.

Key words: Internet of vehicles, connectivity, node degree distribution, complex network, scale-free IoV

中图分类号:

TN92

韩涛, 贺威, 代俊, 左勇, 杨旸, 葛晓虎. 基于无标度网络的车联网连通性研究[J]. 通信学报, 2021, 42(4): 100-108.

Tao HAN, Wei HE, Jun DAI, Yong ZUO, Yang YANG, Xiaohu GE. Connectivity analysis of IoV based on scale-free network[J]. Journal on Communications, 2021, 42(4): 100-108.

图/表 6

图1

图2

表1

仿真参数设置"

参数	值
仿真时间/s	100
仿真区域	10 km×10 km
车辆速度/(km·h^-1)	45~60
车辆节点	100, 200, 300, 500
路径损耗参数 $l_{1}^{(L)}$ , $l_{1}^{(O)}$	1.66, 1.93
路径损耗参数 $l_{2}^{(L)}$ , $l_{2}^{(O)}$ )	2.88, 2.74
节点发送消息的概率P_i	0.05
发射功率/dBm	23
节点成功解码信号的SINR阈值/dB	-13
偏好连接的概率 p_a	0.5
随机连接的概率 p_b	0.5

表1

图3

图4

图5

参考文献 24

[1]	QURESHI K N , DIN S , JEON G ,et al. Internet of vehicles:key technologies,network model,solutions and challenges with future aspects[J]. IEEE Transactions on Intelligent Transportation Systems, 2021,22(3): 1777-1786.
[2]	RASHEED A , GILLANI S , AJMAL S ,et al. Vehicular ad hoc network (VANET):a survey,challenges,and applications[C]// Vehicular Ad-Hoc Networks for Smart Cities. Berlin:Spring, 2017: 39-51.
[3]	REHMAN O , QURESHI R , OULD-KHAOUA M ,et al. Analysis of mobility speed impact on end-to-end communication performance in VANETs[J]. Vehicular Communications, 2020,26: 100278.
[4]	VIRIYASITAVAT W , BAI F , TONGUZ O K . Dynamics of network connectivity in urban vehicular networks[J]. IEEE Journal on Selected Areas in Communications, 2011,29(3): 515-533.
[5]	MOUSA R J , HUSZáK R , SALMAN M A . Enhancing VANET connectivity through a realistic model for RSU deployment on highway[J]. Journal of Physics:Conference Series, 2021,1804(1): 012104
[6]	XIAO H L , ZHANG Q Y , OUYANG S ,et al. Connectivity probability analysis for VANET freeway traffic using a cell transmission model[J]. .IEEE Systems Journal, 2020.
[7]	KOMETANI E , SASAKI T . On the stability of traffic flow (report-I)[J]. Journal of the Operations Research Society of Japan, 1958,2(1): 11-26.
[8]	WANG P F , DI B Y , ZHANG H L ,et al. Platoon cooperation in cellular V2X networks for 5G and beyond[J]. IEEE Transactions on Wireless Communications, 2019,18(8): 3919-3932.
[9]	ZHANG L R , LAKAS A , EL-SAYED H ,et al. Mobility analysis in vehicular ad hoc network (VANET)[J]. Journal of Network and Computer Applications, 2013,36(3): 1050-1056.
[10]	GAO H H , LIU C , LI Y ,et al. V₂VR:reliable hybrid-network-oriented V2V data transmission and routing considering RSUs and connectivity probability[J]. IEEE Transactions on Intelligent Transportation Systems, 2020,PP(99): 1-14.
[11]	CHANDRASEKHARAMENON N P , ANCHAREV B . Connectivity analysis of one-dimensional vehicular ad hoc networks in fading channels[J]. EURASIP Journal on Wireless Communications and Networking, 2012,2012(1): 1-16.
[12]	BOBAN M T , VINHOZA T T V , FERREIRA M ,et al. Impact of vehicles as obstacles in vehicular ad hoc networks[J]. IEEE Journal on Selected Areas in Communications, 2011,29(1): 15-28.
[13]	ABBAS T , SJ?BERG K , KAREDAL J ,et al. A measurement based shadow fading model for vehicle-to-vehicle network simulations[J]. International Journal of Antennas and Propagation, 2015(3): 1-12.
[14]	CHEN R F , ZHONG Z D , LEUNG V C M ,et al. Performance analysis of connectivity for vehicular ad hoc networks with moving obstructions[C]// 2014 IEEE 80th Vehicular Technology Conference. Piscataway:IEEE Press, 2014: 1-5.
[15]	JAIN K , SINGH U , SINGH P ,et al. Hybrid Protocol for Reducing Interference in VANETS[J]. International Journal of Computer Applications, 2017,166(12): 35-38.
[16]	ALBERT R , BARABáSI A L . Statistical mechanics of complex networks[J]. Reviews of Modern Physics, 2002,74(1): 47.
[17]	BARABáSI A L , Albert R . Emergence of scaling in random networks[J]. Science, 1999,286(5439): 509-512.
[18]	BARABáSI A L , BONABEAU E . Scale-free networks[J]. Scientific American, 2003,288(5): 60-69.
[19]	SUN R X , YE J , TANG K ,et al. Big data aided vehicular network feature analysis and mobility models design[J]. Mobile Networks and Applications, 2018,23(6): 1487-1495.
[20]	NABOULSI D , FIORE M . On the instantaneous topology of a large-scale urban vehicular network:the cologne case[C]// Proceedings of the Fourteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing. New York:ACM Press, 2013: 167-176.
[21]	MONTEIRO R , SARGENTO S , VIRIYASITAVAT W ,et al. Improving VANET protocols via network science[C]// 2012 IEEE Vehicular Networking Conference. Piscataway:IEEE Press, 2012: 17-24.
[22]	NABOULSI D , FIORE M . Characterizing the instantaneous connectivity of large-scale urban vehicular networks[J]. IEEE Transactions on Mobile Computing, 2017,16(5): 1272-1286.
[23]	QU X Y , LIU E W , WANG R ,et al. Complex network analysis of VANET topology with realistic vehicular traces[J]. IEEE Transactions on Vehicular Technology, 2020,69(4): 4426-4438.
[24]	ABUELENIN S M , ABUL-MAGD A Y , . Empirical study of traffic velocity distribution and its effect on VANETs connectivity[C]// 2014 International Conference on Connected Vehicles and Expo. Piscataway:IEEE Press, 2014: 391-395.

基于无标度网络的车联网连通性研究

Connectivity analysis of IoV based on scale-free network

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