In this chapter, we discuss the role of federated learning for vehicular networks. Due to the high mobility of autonomous cars, there might not be seamless connectivity of the end-devices within cars with the roadside units, and thus traditional federated learning might not work well. To overcome this challenge, we introduced a dispersed federated learning framework for autonomous driving cars. We formulate a dispersed federated learning cost optimization problem and proposed an iterative scheme. Finally, we present extensive simulation results to validate the proposal.


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    Title :

    Vehicular Networks and Autonomous Driving Cars


    Additional title:

    Wireless Networks


    Contributors:
    Seon Hong, Choong (author) / Khan, Latif U. (author) / Chen, Mingzhe (author) / Chen, Dawei (author) / Saad, Walid (author) / Han, Zhu (author)


    Publication date :

    2021-08-09


    Size :

    42 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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