基于网络效用最大化理论的分布式车联网拥塞控制策略

doi:10.11959/j.issn.1000-436x.2019040

通信学报 ›› 2019, Vol. 40 ›› Issue (2): 82-91.doi: 10.11959/j.issn.1000-436x.2019040

基于网络效用最大化理论的分布式车联网拥塞控制策略

谭国真¹,韩国栋¹,张福新²,丁男¹,刘明剑³

¹ 大连理工大学计算机与科学技术学院，辽宁大连 116024
² 山东科技大学计算机科学与工程学院，山东青岛 266590
³ 大连海洋大学信息工程学院，辽宁大连 116023

修回日期:2018-04-10 出版日期:2019-02-01 发布日期:2019-03-04
作者简介:谭国真（1960- ），男，辽宁大连人，博士，大连理工大学教授、博士生导师，主要研究方向为智能交通和车联网等。|韩国栋（1992- ），男，山东淄博人，大连理工大学硕士生，主要研究方向为车联网信道拥塞控制。|张福新（1981- ），男，山东莱州人，博士，山东科技大学讲师，主要研究方向为车联网、无线网络资源分配、跨层优化。|丁男（1978- ），男，辽宁沈阳人，博士，大连理工大学副教授，主要研究方向为传感网络。|刘明剑（1984- ），男，辽宁大连人，博士，大连海洋大学讲师，主要研究方向为车联网环境下车辆安全预警技术与车联网消息调度器。
基金资助:
国家高科技基金资助项目(2012AA111902);国家自然科学基金资助项目(61471084);山东省自然科学基金资助项目(ZR201709210163);山东科技大学人才引进科研启动基金资助项目(2017RCJJ044)

Distributed congestion control strategy using network utility maximization theory in VANET

Guozhen TAN¹,Guodong HAN¹,Fuxin ZHANG²,Nan DING¹,Mingjian LIU³

¹ The Computer Science Institute,Dalian University of Technology,Dalian 116024,China
² College of Computer Science and Engineering,Shandong University of Science and Technology,Qingdao 266590,China
³ College of Information Engineering,Dalian Ocean University,Dalian 116023,China

Revised:2018-04-10 Online:2019-02-01 Published:2019-03-04
Supported by:
The National High-Tech Projects(2012AA111902);The National Natural Science Foundation of China(61471084);The Natural Science Foundation of Shandong Province(ZR201709210163);The Scientific Research Foundation of Shandong University of Science and Technology for Recruited Talents(2017RCJJ044)

摘要/Abstract

摘要：

协同车辆安全系统依靠周期性广播的单跳数据分组来追踪周围车辆，车辆密度过高会导致信道拥塞，严重影响协同车辆安全系统的性能。现有的拥塞控制策略仅保证网络层的性能，没有考虑车辆不同交通场景下的微观服务需求。为解决该问题，提出了一种基于网络效用最大化理论的分布式拥塞控制策略。该策略首先提出了车联网信道资源分配的网络效用最大化模型，并且提出了反映车辆安全需求的效用函数；然后基于该模型，建立了传输功率固定条件下无线信道资源分配的优化问题；最后为求解该优化问题，设计了分布式拥塞控制算法UBRCC，该算法通过更新车辆的拥塞“价格”求解最优数据分组发送速率，实现了面向单个车辆安全需求的信道资源分配。仿真实验结果表明，UBRCC 算法在控制信道拥塞的同时，能够有效地减小传输时延，确保数据分组可靠发送，满足车辆安全应用的服务需求。

关键词: 协同车辆安全系统, 车联网, 拥塞控制, 公平性, 网络效用最大化

Abstract:

Cooperative vehicle safety system (CVSS) rely on periodical beacons to track neighboring vehicles.High traffic density often causes channel congestion,seriously damaging the performance of CVSS.Existing congestion control strategies aim to ensure the performance in network layer,without considering the service requirements of vehicles in different driving contexts.To solve the problem,a distributed congestion control strategy using network utility maximization (NUM) theory was proposed.First of all,the NUM model for channel resource allocation was introduced.A utility function reflecting vehicle’s safety requirements was proposed in the model.Then under the condition of fixed transmit powers,a optimization problem of channel resource allocation was proposed.Lastly,to solve the optimization problem,a distributed congestion control algorithm named utility-based rate congestion control (UBRCC) algorithm was designed,the algorithm worked out the optimal beaconing rate by updating vehicle’s congestion price,realizing the resource allocation according to vehicle’s safety requirements.Simulation results validate that UBRCC algorithm can efficiently control channel congestion,reduce transmission delay,ensure reliable data transmission and satisfies the requirements of safety applications.

Key words: cooperative vehicle safety systems, VANET, congestion control, fairness, network utility maximization

中图分类号:

TP393

谭国真,韩国栋,张福新,丁男,刘明剑. 基于网络效用最大化理论的分布式车联网拥塞控制策略[J]. 通信学报, 2019, 40(2): 82-91.

Guozhen TAN,Guodong HAN,Fuxin ZHANG,Nan DING,Mingjian LIU. Distributed congestion control strategy using network utility maximization theory in VANET[J]. Journal on Communications, 2019, 40(2): 82-91.

图/表 12

图1

图2

图3

图4

表1

表2

算法参数"

参数	值
最大数据分组发送速率 $R_{v}^{\max} / （个 \cdot s^{- 1} ）$	12
最小数据分组发送速率 $R_{v}^{\min} / （个 \cdot s^{- 1} ）$	4
初始数据分组发送速率 $R_{v}^{i n i t} / （个 \cdot s^{- 1} ）$	4
收敛速度控制参数β	1×10^-6
初始拥塞价格 $λ_{v}^{0}$	2.5×10^-3
算法迭代次数/次	20

表2

图5

图6

图7

图8

图9

图10

参考文献 24

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参数	值
发送速率/(Mbit.s^-1)	4.5
MBP	0.6
竞争窗口大小	32
数据分组大小/B	512
信噪比SINR/dB	4
传输功率/dBm	80
车速更新时间/ s	2
车辆初始速度/ (m.s^-1)	30
司机反应时间/ s	0.5
最小期望碰撞车距d_min/m	10
可接受横向车距d_gap/m	1
车流密度	由0.2辆/m变化到0.4辆/m

基于网络效用最大化理论的分布式车联网拥塞控制策略

Distributed congestion control strategy using network utility maximization theory in VANET

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