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سال انتشار:
2018
عنوان انگلیسی مقاله:
QoE-Driven Big Data Management in Pervasive Edge Computing Environment
ترجمه فارسی عنوان مقاله:
مدیریت داده های بزرگ بر مبنای QoE در محدوده محاسباتی فراگیر لبه
منبع:
IEEE - ISSN 2096-0654 04/06 pp222–233 Volume 1, Number 3, September 2018
نویسنده:
Qianyu Meng, Kun Wang, Xiaoming He, and Minyi Guo
چکیده انگلیسی:
In the age of big data, services in the pervasive edge environment are expected to offer end-users
better Quality-of-Experience (QoE) than that in a normal edge environment. However, the combined impact of the
storage, delivery, and sensors used in various types of edge devices in this environment is producing volumes
of high-dimensional big data that are increasingly pervasive and redundant. Therefore, enhancing the QoE has
become a major challenge in high-dimensional big data in the pervasive edge computing environment. In this
paper, to achieve high QoE, we propose a QoE model for evaluating the qualities of services in the pervasive edge
computing environment. The QoE is related to the accuracy of high-dimensional big data and the transmission
rate of this accurate data. To realize high accuracy of high-dimensional big data and the transmission of accurate
data through out the pervasive edge computing environment, in this study we focused on the following two aspects.
First, we formulate the issue as a high-dimensional big data management problem and test different transmission
rates to acquire the best QoE. Then, with respect to accuracy, we propose a Tensor-Fast Convolutional Neural
Network (TF-CNN) algorithm based on deep learning, which is suitable for high-dimensional big data analysis in
the pervasive edge computing environment. Our simulation results reveal that our proposed algorithm can achieve
high QoE performance.
Key words: Quality-of-Experience (QoE); high-dimensional big data management; deep learning; pervasive edge computing
قیمت: رایگان
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