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Multiple contents offloading mechanism in AI-enabled opportunistic networks
مکانیسم تخلیه محتوای چندگانه در شبکه های فرصت طلب مجهز به هوش مصنوعی-2020 With the rapid growth of mobile devices and the emergence of 5G applications, the burden of cellular
and the use of the licensed band have enormous challenges. In order to solve this problem, opportunity
communication is regarded as a potential solution. It can use unlicensed bands to forward content to users
under delay-tolerance constraints, as well as reduce cellular data traffic. Since opportunity communication is
easily interrupted when User Equipment (UE) is moving, we adopt Artificial Intelligence (AI) to predict the
location of the mobile UE. Then, the meta-heuristic algorithm is used to allocate multiple contents. In addition,
deep learning-based methods almost need a lot of training time. Based on real-time requirements of the
network, we propose AI-enabled opportunistic networks architecture, combined with Mobile Edge Computing
(MEC) to implement edge AI applications. The simulation results show that the proposed multiple contents
offloading mechanism can reduce cellular data traffic through UE location prediction and cache allocation. Keywords: Opportunistic networks | MEC | Offloading | Content caching |
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