Vehicular networks are required to meet strict performance criteria to reliably support safety-critical applications at scale. However, wireless communication technologies that are currently available for vehicles usually have unique sets of limitations in terms of latency, throughput, and/or signal propagation characteristics. A promising solution to break through these limitations is hybrid vehicular networking, in which on-board units in vehicles concurrently make use of multiple types of radios (e.g., DSRC, Wi-Fi, LTE, etc.), dynamically selecting the most suitable network interface(s) according to the performance requirements and network conditions. In this paper, we explore the potential of a quasi-centralized approach to hybrid vehicular networking. Vehicles opportunistically report their positions and channel load measurements to a cloud-based central server when they have access to network infrastructure (e.g., roadside units). Analyzing the wide-scale statistics on road and network conditions, the server derives and distributes recommended network selection strategy for each geographical region, allowing vehicles to make globally-optimized network selection. Through a case study and proof-of-concept simulations, we show the basic feasibility of the concept of cloud-assisted hybrid vehicular networking.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Leveraging cloud intelligence for hybrid vehicular communications


    Contributors:


    Publication date :

    2017-10-01


    Size :

    204900 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Intelligence transportation service using Vehicular Cloud Network

    Abhale, Ashwini B. / Khandelwal, Sumit A. | IEEE | 2016


    DTN hybrid networks for vehicular communications

    Rohrer, Justin P. / Xie, Geoffrey G. | IEEE | 2013


    MmWave Vehicular Beam Alignment Leveraging Online Learning

    Xian, Qingyang / Doufexi, Angela / Armour, Simon | IEEE | 2023


    Hybrid Interface Selection for Heterogeneous Vehicular Communications

    ALTINTAS ONUR / HIGUCHI TAKAMASA | European Patent Office | 2018

    Free access

    Hybrid interface selection for heterogeneous vehicular communications

    ALTINTAS ONUR / HIGUCHI TAKAMASA | European Patent Office | 2019

    Free access