• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.742-753
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• 2022

Cloud computing, which is rapidly growing as one of the core technologies of the 4th industrial revolution, has become the center of global IT trend change, and Docker, a container-based open source platform, is the mainstream for virtualization technology for cloud computing. Therefore, in this paper, research trends based on Docker containers were compared and analyzed, focusing on studies published from March 2013 to July 2022. As a result of the study, first, the number of papers published by year, domestic and foreign research were steadily increasing. Second, the keywords of the study, in domestic research, Docker, Docker Containers, and Containers were in the order, and in foreign research, Cloud Computing, Containers, and Edge Computing were in the order. Third, in the frequency of publishing institutions to estimate research trends, the utilization was the highest in two papers of the Korean Next Generation Computer Society and the Korean Computer Accounting Society. In the overseas research, IEEE Communications Surveys & Tutorials, IEEE Access, and Computer were in the order. Fourth, in the research method, experiments 78(26.3%) and surveys 32(10.8%) were conducted in domestic research. In foreign research, experiments 128(43.1%) and surveys 59(19.9%) were conducted. In the experiment of implementation research, In domestic research, System 25(8.4%), Algorithm 24(8.1%), Performance Measurement and Improvement 16(5.4%) were in the order, In foreign research, Algorithm 37(12.5%), Performance Measurement and Improvement 17(9.1%), followed by Framework 26(8.8%). Through this, it is expected that it will be used as basic data that can lead the research direction of Docker container-based cloud computing such as research methods, research topics, research fields, and technology development.

• KIISE Transactions on Computing Practices
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• v.21 no.9
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• pp.587-595
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• 2015

Several fields of science have traditionally demanded large-scale workflow support, which requires thousands of central processing unit (CPU) cores. In order to support such large-scale scientific workflows, large-capacity cluster systems such as supercomputers are widely used. However, as users require a diversity of software packages and configurations, a system administrator has some trouble in making a service environment in real time. In this paper, we present a container-based cluster management platform and introduce an implementation case to minimize performance reduction and dynamically provide a distributed computing environment desired by users. This paper offers the following contributions. First, a container-based virtualization technology is assimilated with a resource and job management system to expand applicability to support large-scale scientific workflows. Second, an implementation case in which docker and HTCondor are interlocked is introduced. Lastly, docker and native performance comparison results using two widely known benchmark tools and Monte-Carlo simulation implemented using various programming languages are presented.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.125-128
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• 2019

클라우드 가상화에서 최근 가장 많이 사용되는 컨테이너(container) 기술은 성능 향상과 이식성 및 확장성의 특징을 가지고 있다. 본 논문에서는 컨테이너 특성을 살펴보고, Docker 를 포함한 여러 컨테이너들을 비교해 본다. 본 연구의 시스템 아키텍처로, JMS(Java Message Service)기반의 분산 컨테이너 클러스터를 구성하였다. 분산 컨테이너 클러스터 상에서 메시지 처리 속도를 지표로 삼아 컨테이너 수와 Docker engine 의 메모리의 증가에 따른 성능을 비교 분석하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.71-73
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• 2018

소프트웨어 애플리케이션의 가상화를 지원하는 컨테이너(container)는 일반적인 가상머신과 같은 운영체제의 격리된 인스턴스 형태이지만 VM과는 달리 호스트 OS자원을 공유하여 자원을 효율적으로 사용할 수 있고 이식성이 좋으며 배포를 쉽게 할 수 있는 등 장점이 있다. 컨테이너의 중요성과 활용도가 높아지면서 그것을 관리하고 통제하는 오케스트레이션 솔루션도 각광을 받고 있다. 본 논문에서는 Docker에 내장된 오케스트레이션 기능 중 하나인 Docker Swarm이 과도하게 메모리를 사용하는 문제점을 해결하고자 한다. 먼저, Docker Swarm의 구조에서 Manager 노드와 Worker 노드의 서비스를 증가시켜 실행시킨 후 성능을 평가한 후 과점유의 원인을 파악한다. 실험 결과 메모리 과점유의 원인은 컨테이너가 작동을 멈춘 후에도 여전히 메모리를 점유하고 있어 컨테이너를 증가시킬수록 메모리 이용률이 줄어들지 않는 것이 증명되었다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.65-73
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• 2022

Recently, as the Windows system supports the Windows subsystem for Linux (WSL), various researchers have studied to apply a docker container on various systems such as server systems, workstation system and so on. However, in various existing researchers, there is a lack of performance-related indicators to apply the system to each operating system (linux system and windows system). In this paper, we compared a performance comparison and analysis of container-based host operating systems. We configured experimental environments of operating systems for microsoft windows systems and linux systems based on a docker container support. In experimental results, the containers of linux systems reduced the average data latency of dataset 1-6 by 3.9%, 62.16%, 1552.38%, 7.27%, 60.83%, and 1567.2%, compared to the containers on microsoft windows systems.

• KIISE Transactions on Computing Practices
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• v.22 no.2
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• pp.89-94
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• 2016

Recently, cluster computing environments have been in a process of change toward virtualized cluster environments. The change of the cluster environment has great impact on the performance of large volume distributed processing. Therefore, many domestic and international IT companies have invested heavily in research on cluster environments. In this paper, we show how the hypervisor affects the performance of distributed processing of a large volume of data. We present a performance comparison of MapReduce processing in two virtualized cluster environments, one built using the Xen hypervisor and the other built using the container-based Docker. Our results show that Docker is faster than Xen.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.171-172
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• 2020

도커 컨테이너 기반 데이터베이스 플랫폼은 IT 개발자들을 위한 데이터베이스 플랫폼으로써 개발용 데이터베이스를 웹에서 생성할 수 있으며, 개발자는 개발 데이터베이스 세팅을 위한 시간을 줄일 수 있다. 데이터베이스 생성 후, 웹에서 데이터베이스 접속정보를 확인할 수 있으며, 서버상태를 분단위로 확인할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.132-134
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• 2022

클라우드 수요의 지속적인 증가로 인해 효율적인 자원 관리를 수행하는 분산 클라우드 서비스가 주목받고 있으며, 컨테이너 가상화에서 여러 노드에 컨테이너 배치 및 관리를 수행하는 오케스트레이터의 컨테이너 스케줄링 기법에 대한 연구가 진행되고 있다. 하지만 클러스터 집합의 컴퓨팅 자원이 부족할 시 프로세스의 저지연 처리를 보장하기 위한 연구는 활발히 수행되고 있지 않다. 본 연구에서는 Docker Swarm 기반 제한된 컴퓨팅 자원을 가진 클러스터 환경에서 다양한 부하가 발생했을 때 일반 프로세스의 평균 수행 시간 및 평균 지연 처리 정도를 측정 및 분석한다. 이를 통해 오케스트레이터 스케줄링 최적화를 위한 연구 방향성을 제시하며, 향후 관련 연구의 활성화에 기여할 것으로 기대된다.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.10
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• pp.415-420
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• 2017

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.

• Journal of Digital Contents Society
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• v.19 no.3
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• pp.453-460
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• 2018

Virtualization technology is characterized by the ability to isolate the user's system environment and to support the computing resources flexibly and extensively on demand. However, virtualization technology of cloud computing, which is already well known, must overload the guest OS and the hypervisor to manage it. Container technology is emerging to solve such OS-based virtualization problems. This technology can isolate the processes under which the application is running, thus creating a virtualization-like environment with minimal overhead. In this work, we construct a container-based education practice system using Docker instead of the existing cloud-based environment. To do this, we analyze the requirements for the establishment of the training practice environment. We also analyze the functions of the container and study the method to meet the requirements. This can take advantage of the existing flexible and scalable cloud computing. Also, it maximizes the availability of limited resources by minimizing the performance load.