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Analysis of Component Performance using Open Source for Guarantee SLA of Cloud Education System

클라우드 교육 시스템의 SLA 보장을 위한 오픈소스기반 요소 성능 분석

  • Yoon, JunWeon (Department of Supercomputing Center, KISTI) ;
  • Song, Ui-Sung (Department of Computer Education, Busan National University of Education)
  • 윤준원 (한국과학기술정보연구원 슈퍼컴퓨팅본부) ;
  • 송의성 (부산교육대학교 컴퓨터교육과)
  • Received : 2016.12.27
  • Accepted : 2017.02.25
  • Published : 2017.02.28

Abstract

As the increasing use of the cloud computing, virtualization technology have been combined and applied a variety of requirements. Cloud computing has the advantage that the support computing resource by a flexible and scalable to users as they want and it utilized in a variety of distributed computing. To do this, it is especially important to ensure the stability of the cloud computing. In this paper, we analyzed a variety of component measurement using open-source tools for ensuring the performance of the system on the education system to build cloud testbed environment. And we extract the performance that may affect the virtualization environment from processor, memory, cache, network, etc on each of the host machine(Host Machine) and a virtual machine (Virtual Machine). Using this result, we can clearly grasp the state of the system and also it is possible to quickly diagnose the problem. Furthermore, the cloud computing can be guaranteed the SLA(Service Level Agreement).

클라우드의 사용이 보급화 됨에 따라 가상화 기술에 다양한 요구사항이 접목, 적용되고 있다. 클라우드 컴퓨팅의 대표적인 특징은 사용자가 원하는 자원 요구사항에 따라 최적화 된 환경을 구축할 수 있으며, 나아가 확장성에도 유연하게 대처할 수 있다. 이런 장점으로 인해 다양한 분산컴퓨팅 분야에 클라우드 컴퓨팅이 적용, 활용되고 있는 실정이다. 이를 위해 클라우드 환경의 성능 안정성을 보장하는 것이 무엇보다 중요하다. 본 연구에서는 구축된 클라우드 교육 시스템 테스트베드 환경에서 시스템의 성능을 보장하기 위한 다양한 요소성능(metric) 측정을 오픈소스 기반의 툴들을 이용하여 분석하였다. 이를 위해 프로세서, 메모리, 캐시, 네트워크 등 가상화 환경에 영향을 주는 요소 성능을 구분하고, 그 성능을 호스트머신(Host Machine) 및 가상머신(Virtual Machine)에서 각각 측정하였다. 이로서 시스템의 상태를 명확하게 파악할 수 있으며, 문제점을 빠르게 진단하여 가용성을 증대시키고 나아가 클라우드 컴퓨팅의 SLA(Service Level Agreement) 수준을 보장할 수 있다.

Keywords

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