TY  - JOUR
T1  - The Method Using Reduced Classification Models for Distributed Processing of CNN Models in Multiple Edge Devices
AU  - Kim, Junyoung 
AU  - Jeon, Jongho 
AU  - Kee, Minkwan 
AU  - Park, Gi-Ho 
JO  - Journal of KIISE, JOK
PY  - 2020
DA  - 2020/1/14
DO  - 10.5626/JOK.2020.47.8.787
KW  - machine learning
KW  - deep learning
KW  - convolutional neural networks
KW  - edge computing
KW  - distributed computing
AB  - Recently, there have been increasing demands for edge computing that processes data at the end of the network wherein data is collected because of various problems such as network load caused by a large amount of data transfer to a cloud server. However, it is difficult for edge devices to use deep learning applications used in cloud servers because most edge devices at the end of the network have limited performance. To overcome these problems, this paper proposes a distributed processing method that uses reduced classification models to jointly perform inferences on multiple edge devices. The reduced classification models have compressed model weights, and perform inferences for some parts of the total classification labels. The experimental results confirmed that the accuracy of the result of the proposed distributed processing method is similar to the accuracy of the result of the original model, even if the proposed reduced classification models had much less parameters than those of the original model.