• DocumentCode
    50241
  • Title

    Location-Based Crowdsourcing for Vehicular Communication in Hybrid Networks

  • Author

    Wu, Dalei ; Zhang, Ye ; Bao, L. ; Regan, Amelia

  • Author_Institution
    Department of Computer Science, University of California, Irvine , CA, USA
  • Volume
    14
  • Issue
    2
  • fYear
    2013
  • fDate
    Jun-13
  • Firstpage
    837
  • Lastpage
    846
  • Abstract
    It is a challenge to design efficient routing protocols for vehicular ad hoc networks (VANETs) because of their highly dynamic properties. We address the vehicular communication problem in urban hybrid networks and present a hybrid routing scheme for data dissemination in VANETs. Location-based crowdsourcing of nearby roadside units (RSUs) has been applied to the infrastructural support of inter-vehicle, vehicle-to-roadside, and inter-roadside communications in hybrid VANETs. The combination of RSU resources and ad hoc networks involves an online probabilistic RSU retrieval algorithm that uses coarse- and fine-grained localization to estimate the number and location of available RSUs; a network coding based multicast routing for dense VANETs using maximum distance separation (MDS) code and local topology information from the forwarding set to achieve robust communication and max-flow min-cut data dissemination; an application of opportunistic routing, using a carry-and-forward scheme to solve the forwarding disconnection problem in sparse VANETs; and a routing switch mechanism to guarantee quality of service (QoS) under various network connectivity and deployment configurations. The performance of our hybrid routing scheme is evaluated using both simulations and real testbed experiments.
  • Keywords
    Crowdsourcing; localization; multicast routing; opportunistic routing; vehicular communication;
  • fLanguage
    English
  • Journal_Title
    Intelligent Transportation Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1524-9050
  • Type

    jour

  • DOI
    10.1109/TITS.2013.2243437
  • Filename
    6514521