A Fluid Mechanics-Based Data Flow Model to Estimate VANET Capacity
A Fluid Mechanics-Based Data Flow Model to Estimate VANET Capacity
复制标题
基于流体力学的数据流模型来估计 VANET 容量
DOI：
10.1109/tits.2019.2921074
复制
发表时间：
2020-06-01
影响因子：
8.5
通讯作者：
Duan, Hua
中科院分区：
文献类型：
--
作者：
Cheng, Jiujun;Yuan, Guiyuan;Duan, Hua
对于带宽有限且具有高度动态特性的车载自组织网络（VANET），准确估计数据传输能力对其运行至关重要。传统无线网络的移动行为与VANET的移动行为不同，传统无线网络的研究成果并不直接适用于VANET。现有的VANET容量估计研究大多集中在渐近描述上。其中，车辆节点发送和接收的消息由数据包组成，车辆节点只能沿道路移动。本文提出了一种精确的VANET容量建模和计算方法。我们将车辆节点转换为数据包，然后将可以沿着道路移动的数据包抽象为虚拟管道中的数据流。然后，推导了基于流体力学的数据流模型，提出了容量计算方程。根据网络规模，网络容量分为线性增长、维护和下降三个阶段。本文论证了基于数据流模型的能力与仿真结果一致。
Accurately estimated data transmission ability is important in operating a vehicular ad-hoc network (VANET), which has limited bandwidth and highly dynamic typology. The mobility behavior of traditional wireless networks is different from VANET's, and existing results on the former are not applicable to VANET directly. Most existing studies on VANET capacity estimation focus on asymptotic descriptions. In them, messages sent and received by vehicle nodes are composed of data packets, and vehicle nodes can move along roads only. In this paper, a modeling and calculation approach for accurate VANET capacity is proposed. We transfer vehicle nodes to data packets and then abstract data packets that can move along roads into data flow in virtual pipelines. Then, we derive a fluid mechanics-based data flow model and propose capacity calculation equations. According to network scale, network capacity is divided into following three stages: linear growth, maintenance, and decline. This paper demonstrates that the data flow model-based capacity is consistent with that of simulation results.