In vehicular crowdsensing (VCS) applications, vehicular participants should be carefully selected to meet the limited operation budget while providing sufficient quality of sensing. In this paper, we propose a matching based vehicular participant recruiting (MVP) strategy. The MVP strategy in-centivizes detouring vehicles to the target region, which allows the maximization of the sensing quality under the given VCS operation budget. The preliminary simulation results based on real traces demonstrate that MVP outperforms the existing vehicular crowdsensing strategy.


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    Title :

    Poster: A Vehicular Participant Recruiting Strategy for Improving Sensing Quality in Vehicular Crowdsensing


    Contributors:


    Publication date :

    2019-12-01


    Size :

    475268 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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