Chanho Yong, Sang-Ho Na, Pill-Woo Lee, Eui-Nam Huh

KIPS Transactions on Computer and Communication Systems, Vol. 6, No. 10, pp. 415-420, Oct. 2017
10.3745/KTCCS.2017.6.10.415,   PDF Download:
Keywords: Docker, Container, Layered File System, Docker Image, Machine Learning
Abstract

Virtualization technique of OS-level is a new paradigm for deploying applications, and is attracting attention as a technology to replace traditional virtualization technique, VM (Virtual Machine). Especially, docker containers are capable of distributing application images faster and more efficient than before by applying layered image structures and union mount point to existing linux container. These characteristics of containers can only be used in layered file systems that support snapshot functionality, so it is required to select appropriate layered file systems according to the characteristics of the containerized application. We examine the characteristics of representative layered file systems and conduct write performance evaluations of each layered file systems according to the operating principles of the layered file system, Allocate-on-Demand and Copy-up. We also suggest the method of determining a appropriate layered file system principle for unknown containerized application by learning block I/O usage history of each layered file system principles in artificial neural network. Finally we validate effectiveness of artificial neural network created from block I/O history of each layered file system principles.

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