MANETs are gathering of wireless devices which vigorously make an ad hoc network in many conditions as adversity release, vital consultation or military assignment even deprived of the sustenance of an infrastructure for the network. A topology of the network might alter often because the nodes either can connect or vacate the network of your own free will. In mobile ad hoc networks, nodes synchronize to each other for the maintenance of the connections amongst them. Transmission of data to the destination node from a source node is transmitted through intermediary nodes. The node can perform as host and router simultaneously.

    In this chapter, we will discuss the best way which can transmit the nodes effectively from source to destination node reduce computational complexity and increase detection accuracy. In this chapter and a discussion for researchers to apply machine learning to complications in ad hoc networks and various protocols of MANETs. The explanation of various machine learning approaches for use in wireless ad hoc networks is given, classifying the most appropriate necessities, recompenses and signifying their area. This chapter also appraises the most important current and on‐going research in this domain. The accessible mechanism is estimated in terms of their quality.


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    Titel :

    Role of Machine Learning for Ad Hoc Networks


    Beteiligte:
    Singh, Gurinder (Herausgeber:in) / Jain, Vishal (Herausgeber:in) / Chatterjee, Jyotir Moy (Herausgeber:in) / Gaur, Loveleen (Herausgeber:in) / Gaba, Shivani (Autor:in) / Aggarwal, Alankrita (Autor:in) / Nagpal, Shally (Autor:in)


    Erscheinungsdatum :

    2021-04-22


    Format / Umfang :

    23 pages




    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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