In the Internet of Vehicles (IoV), the Internet of Things (IoT) is integrated with Vehicular Ad hoc NETworks (VANET). This enables gathering, processing and sharing of lots of information (regarding vehicles, roads and their surroundings) through the Internet and hence, helps in making intelligent decisions. On the other hand, Software Defined Networking (SDN) has the capability of designing a flexible programmable IoV network that can foster innovation and reduce complexity. Applying SDN in IoV will be useful, as SDN enabled IoV devices can be controlled seamlessly from an external server (called a controller) which can be located in the cloud and may have computational resources to run resource-intensive algorithms, making intelligent decisions. This chapter provides an introduction about SDN, describes the benefits of integrating SDN in IoV and reports the recent advances. It also presents an Artificial Intelligence (AI) based architecture and open challenges. Finally, the chapter presents an automatic configuration method with which SDN can be deployed automatically in IoV without any manual configuration. The experiments are performed on a publicly available European testbed using an emulator for wireless SDN networks. Experiments are conducted for automatic configuration of SDN in IoV network’s topologies and for data collection in SDN enabled IoV. The results show the effectiveness of the proposed automatic configuration method. Furthermore, AI-assisted intelligent decisions supported by SDN enabled IoV are introduced. The challenges and solutions presented in this chapter may have a huge impact on the speed at which IoV infrastructure can efficiently evolve with market evolution.


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    Titel :

    Towards Artificial Intelligence Assisted Software Defined Networking for Internet of Vehicles


    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) / Sharma, Sachin (Autor:in)


    Erscheinungsdatum :

    2021-06-10


    Format / Umfang :

    32 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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