دانلود مقاله انگلیسی رایگان:معماری مدل قابل اطمینان کانال دارای قابلیت هوش مصنوعی برای شبکه های خودروی محاسباتی مه - 2020
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  • AI-Enabled Reliable Channel Modeling Architecture for Fog Computing Vehicular Networks AI-Enabled Reliable Channel Modeling Architecture for Fog Computing Vehicular Networks
    AI-Enabled Reliable Channel Modeling Architecture for Fog Computing Vehicular Networks

    سال انتشار:

    2020


    عنوان انگلیسی مقاله:

    AI-Enabled Reliable Channel Modeling Architecture for Fog Computing Vehicular Networks


    ترجمه فارسی عنوان مقاله:

    معماری مدل قابل اطمینان کانال دارای قابلیت هوش مصنوعی برای شبکه های خودروی محاسباتی مه


    منبع:

    IEEE - IEEE Wireless Communications;2020;27;2;10.1109/MWC.001.1900311


    نویسنده:

    Ali Hassan Sodhro,Gul Hassan Sodhro, Mohsen Guizani, Sandeep Pirbhulal, and Azzedine Boukerche


    چکیده انگلیسی:

    Artificial intelligence (AI)-driven fog computing (FC) and its emerging role in vehicular networks is playing a remarkable role in revolutionizing daily human lives. Fog radio access networks are accommodating billions of Internet of Things devices for real-time interactive applications at high reliability. One of the critical challenges in today’s vehicular networks is the lack of standard wireless channel models with better quality of service (QoS) for passengers while enjoying pleasurable travel (i.e., highly visualized videos, images, news, phone calls to friends/relatives). To remedy these issues, this article contributes significantly in four ways. First, we develop a novel AI-based reliable and interference-free mobility management algorithm (RIMMA) for fog computing intra-vehicular networks, because traffic monitoring and driver’s safety management are important and basic foundations. The proposed RIMMA in association with FC significantly improves computation, communication, cooperation, and storage space. Furthermore, its self-adaptive, reliable, intelligent, and mobility-aware nature, and sporadic contents are monitored effectively in highly mobile vehicles. Second, we propose a reliable and delay-tolerant wireless channel model with better QoS for passengers. Third, we propose a novel reliable and efficient multi-layer fog driven inter-vehicular framework. Fourth, we optimize QoS in terms of mobility, reliability, and packet loss ratio. Also, the proposed RIMMA is compared to an existing competitive conventional method (i.e., baseline). Experimental results reveal that the proposed RIMMA outperforms the traditional technique for intercity vehicular networks


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 8
    حجم فایل: 725 کیلوبایت

    قیمت: رایگان


    توضیحات اضافی:




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