Hyunchul Lee, Sungmin Lee, Kangseok Kim

KIPS Transactions on Software and Data Engineering, Vol. 9, No. 6, pp. 177-186, Jun. 2020
https://doi.org/10.3745/KTSDE.2020.9.6.177,   PDF Download:
Keywords: Deep Learning, Serverless Computing, AWS Lambda Server, Cold Start Time, capacity limitation
Abstract

Recent advances in deep learning technology have improved image recognition performance in the field of computer vision, and serverless computing is emerging as the next generation cloud computing technology for event-based cloud application development and services. Attempts to use deep learning and serverless computing technology to increase the number of real-world image recognition services are increasing. Therefore, this paper describes how to develop an efficient deep learning based image recognition service system using serverless computing technology. The proposed system suggests a method that can serve large neural network model to users at low cost by using AWS Lambda Server based on serverless computing. We also show that we can effectively build a serverless computing system that uses a large neural network model by addressing the shortcomings of AWS Lambda Server, cold start time and capacity limitation. Through experiments, we confirmed that the proposed system, using AWS Lambda Serverless Computing technology, is efficient for servicing large neural network models by solving processing time and capacity limitations as well as cost reduction.

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