A Fluid Mechanics-Based Data Flow Model to Estimate VANET Capacity

Jiujun Cheng*, Guiyuan Yuan, Mengchu Zhou, Shangce Gao*, Cong Liu, Hua Duan

*この論文の責任著者

研究成果: ジャーナルへの寄稿学術論文査読

52 被引用数 (Scopus)

抄録

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.

本文言語英語
論文番号8738878
ページ(範囲)2603-2614
ページ数12
ジャーナルIEEE Transactions on Intelligent Transportation Systems
21
6
DOI
出版ステータス出版済み - 2020/06

ASJC Scopus 主題領域

  • 自動車工学
  • 機械工学
  • コンピュータ サイエンスの応用

フィンガープリント

「A Fluid Mechanics-Based Data Flow Model to Estimate VANET Capacity」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル