Internet of things (IoTs) has been emerging significantly in recent years and has its impact on different industries, one of such is the automotive industry. In automotive industry, Internet of Vehicles (IoVs) gain considerable attention as it is one of the important constituents of IoTs. There are different scenarios with different network requirements to be considered in IoVs. For instance, safety messages require low latency network, while on the other hand, infotainment services demand high bandwidth network. For such various requirements, the network should be able to allocate appropriate resources to accomplish the desired service. One of the promising technologies that is leveraged to fulfil such goal is Network Slicing. With network slicing, the underlying infrastructure is divided into multiple slices each equipped with required resources to meet specific need. To slice the network, the infrastructure should be controllable in a way that allow a central unit to guide the slicing process. For this purpose, Software-defined Networking (SDN) is utilised to decouple the control plane from the data plane, allowing a separate unit to take control. In this chapter, we discuss vehicular SDN slicing and how to boost it with intelligent capabilities using recent advances in machine and deep learning.


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    Titel :

    Cross Network Slicing in Vehicular Networks


    Weitere Titelangaben:

    Internet of Things: Tech., Communicat., Computing


    Beteiligte:
    Magaia, Naercio (Herausgeber:in) / Mastorakis, George (Herausgeber:in) / Mavromoustakis, Constandinos (Herausgeber:in) / Pallis, Evangelos (Herausgeber:in) / Markakis, Evangelos K. (Herausgeber:in) / Ibraheem, Amani (Autor:in)


    Erscheinungsdatum :

    2021-06-10


    Format / Umfang :

    39 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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