Journal of Xidian University ›› 2021, Vol. 48 ›› Issue (3): 40-48.doi: 10.19665/j.issn1001-2400.2021.03.005

• Advances in Vehicular Network Technologies • Previous Articles     Next Articles

Method for estimation of vehicular network traffic for smart transportations

LING Min1,2(),LUO Ying3(),YUAN Liang4(),JIN Chuanxue5()   

  1. 1. Department of Aviation Manufacturing Engineering,Chengdu Aeronautic Polytechnic,Chengdu 610100,China
    2. School of Information and Communication Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China
    3. Information Center,Chengdu Aeronautic Polytechnic,Chengdu 610100,China
    4. Chengdu Panfeng Technology LTD,Co.,Chengdu 610100,China
    5. National Key Laboratory of Scinece and Technology on Communications,University of Electronic Science and Technology of China,Chengdu 611731,China
  • Received:2020-10-19 Online:2021-06-20 Published:2021-07-05

Abstract:

With the rapid deployment of 5G networks,the Internet of Vehicles (IoV),Internet of Things (IoT),and edge computing have made a great progress,which leads to vehicular network traffic measurements facing many challenges.To this end,the present paper studies the vehicular network traffic estimation problem for smart cities.A software-defined network (SDN)-based vehicular network traffic estimation method is proposed.A coarse-grained measurement value via an SDN architecture is designed.A fine-grained measurement model based on the autoregressive moving average (ARMA) model is constructed.Finally,a heuristic algorithm is presented to obtain accurate estimation results for vehicular network traffic.Simulation results indicate that the method proposed in this paper is feasible and effective.

Key words: smart city, internet of vehicles, edge computing, software-defined networking, network measurement

CLC Number: 

  • TP393