Abstract

Cloud computing model is very powerful in massive data processing and comprehensive analysis, but there are still limitations in the new application scenarios. The proposed edge computing is a good supplement to the shortcomings of cloud computing, but it cannot replace cloud computing. This paper proposes a computing structure based on fusion of cloud computing and edge computing, which organically combines cloud computing technology and edge computing technology, complements each other's advantages, and provides a software and hardware support architecture for the electromagnetic information processing. At the same time, a distributed deep learning algorithm based on edge computing is proposed with considering the combination of edge computing technology and deep learning method. With depth feature extraction and compression coding technology, the communication cost between sensing device and cloud center is reduced. And the computing cooperation between edge device and fusion center is used to speed up the response speed of the system. Finally the delay and energy consumption of the system is reduced and the accuracy of target recognition is guaranteed.

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