A deep learning framework based on 5G edge computing with its applications

doi:10.12267/j.issn.2096-5931.2021.04.017

Abstract

Abstract: Aiming to mitigate the training difficulty of deep neural models at the edge of network, this paper introduces a deep learning model training framework based on 5G edge computing. The presented training framework connects smart devices and performs data communication via the 5G edge computing access network. The model training is firstly implemented in edge computing nodes using local data, and then the model parameters are collected and globally updated in the central server. This scenario ensures the diversity of data sets for training, reduces network􀆳s pressure and protects privacy of local data. Thus, it is a promising edge computing architecture for deep learning.

Key words: 5G, edge computing, deep learning, edge intelligence, medical edge cloud

LI Xiaomin. A deep learning framework based on 5G edge computing with its applications[J]. Information and Communications Technology and Policy, 2021, 47(4): 93-96.

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http://ictp.caict.ac.cn/EN/10.12267/j.issn.2096-5931.2021.04.017

http://ictp.caict.ac.cn/EN/Y2021/V47/I4/93

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