车载自组织网络中基于竞争的时分多址MAC协议  

Contention-based Time Division Multiple Access MAC Protocol in Vehicular Ad Hoc Networks

在线阅读下载全文

作  者:张本宏[1] 吴浩浩 俞磊 ZHANG Benhong;WU Haohao;YU Lei(School of Computer Science and Information Engineering,Hefei University of Technology,Hefei 230601,China;School of Medical Information Technology,Anhui University of Chinese Medicine,Hefei 230012,China)

机构地区:[1]合肥工业大学计算机与信息学院,合肥230601 [2]安徽中医药大学医药信息工程学院,合肥230012

出  处:《计算机工程》2021年第5期154-159,共6页Computer Engineering

基  金:国家自然科学基金(61701005);安徽省科技重大专项(201903a05020049)。

摘  要:车辆的高速移动及网络拓扑变化频繁等特性,使得可靠的介质访问控制(MAC)协议仍难满足车载自组织网络的低延迟和高吞吐量的要求。提出一种基于竞争的时分多址MAC协议,将道路按照通信半径分段,周期性地为每个路段的车辆组织通信,每个通信周期根据功能分为静态段和动态段两部分,静态段使用时分复用的方式进行通信,动态段用于新接入的车辆竞争静态段中的发送时隙。仿真实验结果表明,与DTMAC协议相比,该协议能够提高数据传输的吞吐量,降低车辆之间发生冲突的概率,减少新加入车辆发送数据的等待时延。The high speed of vehicle movement and fast change of network topology make it a challenge to design a reliable Medium Access Control(MAC)protocol to meet the low latency and high throughput requirements of Vehicular Ad Hoc Networks(VANETs).This paper proposes a contention-based Time Division Multiple Access(TDMA)MAC protocol.First,the road is segmented according to the communication radius of vehicles,and then the vehicles in each segment are organized to communicate in a periodic manner.Functionally,each communication period is divided into the static segment and dynamic segment.The former is used for communication by time division multiplexing,and the latter is used for competing for time slots of transmission in the static segment to newly added vehicles.Simulation results show that compared with the DTMAC protocol,this protocol can significantly improve the data transmission throughput,decrease the probability of collision between vehicles,and reduce the waiting time of data sent by newly added vehicles.

关 键 词:车载自组织网络 介质访问控制协议 分布式调度 通信竞争 时隙分配 

分 类 号:TP393[自动化与计算机技术—计算机应用技术]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象