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Modeling of Virtual Switch in Cloud System

클라우드 시스템의 가상 스위치 모델링

  • Received : 2013.12.01
  • Accepted : 2013.12.20
  • Published : 2013.12.28

Abstract

Virtualization is a promising approach to consolidating multiple online services onto a smaller number of computing resources. A virtualized server environment allows computing resources to be shared among multiple performance isolated platforms called virtual machines. Through server virtualization software, applications servers are encapsulated into VMs, and deployed with APIs on top generalized pools of CPU and memory resources. Networking and security have been moved to a software abstraction layer that transformed computing, network virtualization. And it paves the way for enterprise to rapidly deploy networking and security for any application by creating the virtual network. Stochastic reward net (SRN) is an extension of stochastic Petri nets which provides compact modeling facilities for system analysis. In this paper, we develop SRN model of network virtualization based on virtual switch. Measures of interest such as switching delay and throughput are considered. These measures are expressed in terms of the expected values of reward rate functions for SRNs. Numerical results are obtained according to the virtual switch capacity and number of active VMs.

가상화는 다중의 온라인 서비스를 소규모의 컴퓨팅 자원에 배치하는 혁신적인 접근방식이다. 가상화된 서버 환경은 가상머신 (virtual machine: VM)으로 불리는 플랫폼의 다중 성능사이에 공유되는 컴퓨팅 자원들을 허용한다. 서버 가상화를 통해 응용 서버는 가상머신 으로 인캡슐 되었으며 CPU나 메모리 자원 풀에 API와 함께 재배치되었다. 네트워킹과 보안은 네트워크 가상화라는 새로운 소프트웨어 추상화 계층으로 이동하기 시작했으며, 가상 네트워크를 생성함으로써 여러 응용에 대하여 네트워킹과 보안을 빠르게 배치할 수 있게 되었다. SRN은 추계적 페트리 네트의 확장형으로 시스템 분석을 위한 함축된 모델링 기능을 제공한다. 본 논문에서는, 가상 스위치를 기반으로 한 네트워크 가상화 SRN 모델을 개발하고 모델에서 관심 있는 성능지표인 스위칭 지연과 처리율에 대한 수치결과를 가상 스위치 용량과 실행 중인 가상머신 수에 따라 구한다. 이들 성능지표는 SRN 모델에서 적절한 보상율을 제공하는 함수의 기댓값으로 표현되어 그 해가 구해진다.

Keywords

References

  1. Sushil Bhardwaj, Leena Jain, Sandeep Jain, "Cloud Computing: a Study of Infrastructure as a Service (IaaS)", International Journal of Engineering and Information Technology, vol. 2, no. 1, pp. 60-63, 2010
  2. Amazon elastic compute cloud: http://aws.amazon.com/ecs2. Accessed 03 March 2011
  3. H. Castro, M. Villamizar, "Green flexible opportunistic computing with task consolidation and virtualization," Cluster Computing, Vol. 16, pp.545-557, 2013 https://doi.org/10.1007/s10586-012-0222-y
  4. Alin Zhong, H. Jin, S. Wu, X. Shi, "Performance implications of non-uniform VCP-PCPU mapping in virtualization environment," Cluster Computing, Vol. 16, pp.347-358, 2013 https://doi.org/10.1007/s10586-012-0199-6
  5. Microsoft Virtualization Management. www.microsoft.com/VIRTUALIZATION/solution -tech-management.mspx
  6. http://www.vmware.com/support/Performance Best Practicies for VMware vSphere5.1, VMware, 2012
  7. http::/blogs.vmware.com/vmware/2013/03/ vmware-nsx-netwrok-virtualization.html
  8. http://www.cisco.com/en/US/netsol/ns658/#-tab-a
  9. Cheul Woo Ro, Kyung Min Kim, "Stochastic Petri nets Modeling Methods of Channel Allocation in Wireless Networks", IJOC (International Journal of Contents), Vol.4, No.3, 2008.9 https://doi.org/10.5392/IJoC.2008.4.3.020
  10. G. Ciardo and K. S. Trivedi, "A decomposition approach for stochastic reward net models," Performance Evaluation, Vol 18, No. 1, pp.37-59, 1993. https://doi.org/10.1016/0166-5316(93)90026-Q
  11. G. Giardo, K. S. Trivedi: SPNP Users Manual Version 6.0. Technical report, Duke Univ., 1999
  12. Y.H.Kim, Technical Trends of Network Virtualization in Future Internet, Trends Analysis of Electronc Communication, ETRI , Vol. 25, No.1, 2010.2
  13. Fang Ha0, T.V. Lakshman, S. Mukherjee, and H. Song, Enhancing Dynamic Cloud-based ervices using Network Virtualization, VISA09, 2009.8
  14. Y. Liao, D. Yin, and L. Ga, PdP: Parallelizing Data Plane in Virtual Network Substate, VISA09, 2009.8
  15. Yang C. and C.W.Ro, "Adaptive Scheduling for QoS-based Virtual Machine Management in Cloud Computing", International Journal of Contents, vol. 8, no.4, pp. 7-11, 2012 https://doi.org/10.5392/IJoC.2012.8.4.007