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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    Titel :

    Vehicular Networks and Autonomous Driving Cars


    Weitere Titelangaben:

    Wireless Networks


    Beteiligte:
    Seon Hong, Choong (Autor:in) / Khan, Latif U. (Autor:in) / Chen, Mingzhe (Autor:in) / Chen, Dawei (Autor:in) / Saad, Walid (Autor:in) / Han, Zhu (Autor:in)


    Erscheinungsdatum :

    09.08.2021


    Format / Umfang :

    42 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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