دانلود مقاله انگلیسی رایگان:RL-OPRA: یادگیری تقویتی برای تخصیص منابع آنلاین و پیشگیرانه فیلم های زنده با منابع انسانی - 2020
دانلود بهترین مقالات isi همراه با ترجمه فارسی
دانلود مقاله انگلیسی یادگیری تقویتی رایگان
  • RL-OPRA: Reinforcement Learning for Online and Proactive Resource Allocation of crowdsourced live videos RL-OPRA: Reinforcement Learning for Online and Proactive Resource Allocation of crowdsourced live videos
    RL-OPRA: Reinforcement Learning for Online and Proactive Resource Allocation of crowdsourced live videos

    سال انتشار:

    2020


    عنوان انگلیسی مقاله:

    RL-OPRA: Reinforcement Learning for Online and Proactive Resource Allocation of crowdsourced live videos


    ترجمه فارسی عنوان مقاله:

    RL-OPRA: یادگیری تقویتی برای تخصیص منابع آنلاین و پیشگیرانه فیلم های زنده با منابع انسانی


    منبع:

    Sciencedirect - Elsevier - Future Generation Computer Systems, 112 (2020) 982-995. doi:10.1016/j.future.2020.06.038


    نویسنده:

    Emna Baccour a,∗, Aiman Erbad a, Amr Mohamedb, Fatima Haouari b, Mohsen Guizani b, Mounir Hamdi a


    چکیده انگلیسی:

    With the advancement of rich media generating devices, the proliferation of live Content Providers (CP), and the availability of convenient internet access, crowdsourced live streaming services have witnessed unexpected growth. To ensure a better Quality of Experience (QoE), higher availability, and lower costs, large live streaming CPs are migrating their services to geo-distributed cloud infrastructure. However, because of the dynamics of live broadcasting and the wide geo-distribution of viewers and broadcasters, it is still challenging to satisfy all requests with reasonable resources. To overcome this challenge, we introduce in this paper a prediction driven approach that estimates the potential number of viewers near different cloud sites at the instant of broadcasting. This online and instant prediction of distributed popularity distinguishes our work from previous efforts that provision constant resources or alter their allocation as the popularity of the content changes. Based on the derived predictions, we formulate an Integer-Linear Program (ILP) to proactively and dynamically choose the right data center to allocate exact resources and serve potential viewers, while minimizing the perceived delays. As the optimization is not adequate for online serving, we propose a real-time approach based on Reinforcement Learning (RL), namely RL-OPRA, which adaptively learns to optimize the allocation and serving decisions by interacting with the network environment. Extensive simulation and comparison with the ILP have shown that our RL-based approach is able to present optimal results compared to heuristic-based approaches.
    Keywords: Live streaming | QoE | Geo-distributed clouds | Machine and reinforcement learning


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 14
    حجم فایل: 2161 کیلوبایت

    قیمت: رایگان


    توضیحات اضافی:




اگر این مقاله را پسندیدید آن را در شبکه های اجتماعی به اشتراک بگذارید (برای به اشتراک گذاری بر روی ایکن های زیر کلیک کنید)

تعداد نظرات : 0

الزامی
الزامی
الزامی
rss مقالات ترجمه شده rss مقالات انگلیسی rss کتاب های انگلیسی rss مقالات آموزشی
logo-samandehi