سال انتشار:

2020

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عنوان انگلیسی مقاله:

Edge computational task offloading scheme using reinforcement learning for IIoT scenario

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ترجمه فارسی عنوان مقاله:

طرح بارگیری وظیفه محاسباتی لبه با استفاده از یادگیری تقویتی برای سناریوی IIoT

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منبع:

Sciencedirect - Elsevier - ICT Express, Corrected proof. doi:10.1016/j.icte.2020.06.002

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نویسنده:

Md. Sajjad Hossain, Cosmas Ifeanyi Nwakanma, Jae Min Lee, Dong-Seong Kim

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چکیده انگلیسی:

In this paper, end devices are considered here as agent, which makes its decisions on whether the network will offload the computation tasks to the edge devices or not. To tackle the resource allocation and task offloading, paper formulated the computation resource allocation problems as a sum cost delay of this framework. An optimal binary computational offloading decision is proposed and then reinforcement learning is introduced to solve the problem. Simulation results demonstrate the effectiveness of this reinforcement learning based scheme to minimize the offloading cost derived as computation cost and delay cost in industrial internet of things scenarios.
Keywords: Edge computing | Industrial IoT | Offloading | Reinforcement learning

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قیمت: رایگان

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توضیحات اضافی:

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