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Computing

, Volume 97, Issue 11, pp 1121–1140 | Cite as

Eucalyptus-based private clouds: availability modeling and comparison to the cost of a public cloud

  • Jamilson Dantas
  • Rubens Matos
  • Jean Araujo
  • Paulo Maciel
Article

Abstract

High availability in cloud computing services is essential for maintaining customer confidence and avoiding revenue losses due to SLA violation penalties. Since the software and hardware components of cloud infrastructures may have limited reliability, the use of redundant components and multiple clusters may be required to achieve the expected level of dependability while also increasing the computational capacity. A drawback of such improvements is the respective impact on the capital and increase in acquisition and operational costs. This paper presents availability models for private cloud architectures based on Eucalyptus platform, and presents a comparison of costs between these architectures and similar infrastructure rented from a public cloud provider. Metrics for capacity-oriented availability and system steady-state availability are used to compare architectures with distinct numbers of clusters. A heterogeneous hierarchical modeling approach is employed to represent the systems considering both hardware and software failures. The results highlight that improvements on the availability are not significant when increasing the system to more than two clusters. The analysis also shows that the average available capacity is close to the maximum possible capacity in all architectures, and that it takes 18 months, in average, for these private cloud architectures to pay off the cost equivalent to the computational capacity rented from a public cloud.

Keywords

Cloud computing Availability Capacity oriented availability Analytical models 

Mathematics Subject Classification

60J20 68M15 68M01 

References

  1. 1.
    Amazon (2012) Amazon elastic block store (EBS). Amazon.com, Inc. http://aws.amazon.com/ebs
  2. 2.
    Amazon (2012) Amazon elastic compute cloud (EC2). Amazon.com, Inc. http://aws.amazon.com/ec2
  3. 3.
    Amazon (2014) Amazon ec2 pricing. Amazon Inc. http://aws.amazon.com/ec2/pricing/
  4. 4.
    Armbrust M, Fox A, Griffith R, Joseph AD, Katz R, Konwinski A, Lee G, Patterson D, Rabkin A, Stoica I et al (2010) A view of cloud computing. Commun ACM 53(4):50–58CrossRefGoogle Scholar
  5. 5.
    Avizienis A, Laprie JC, Randell B, Landwehr C (2004) Basic concepts and taxonomy of dependable and secure computing. IEEE Trans Dependable Secur Comput 1(1):11–33CrossRefGoogle Scholar
  6. 6.
    Callou G, Maciel P, Tutsch D, Ferreira J, Araújo J, Souza R (2013) Estimating sustainability impact of high dependable data centers: a comparative study between brazilian and us energy mixes. Computing 95(12):1137–1170CrossRefGoogle Scholar
  7. 7.
    Callou G, Maciel P, Tutsch D, Araujo J (2012) Models for dependability and sustainability analysis of data center cooling architectures. In: 20121 IEEE/IFIP 42nd international conference on dependable systems and networks workshops (DSN-W). IEEE, pp 1–6Google Scholar
  8. 8.
    Chaudhary V, Cha M, Walters J, Guercio S, Gallo S (2008) A comparison of virtualization technologies for hpc. In: 22nd international conference on advanced information networking and applications, 2008. AINA 2008. IEEE, pp 861–868Google Scholar
  9. 9.
    Chen R, Bastani FB (1994) Warm standby in hierarchically structured process-control programs. IEEE Trans Softw Eng 20(8):658–663CrossRefGoogle Scholar
  10. 10.
    Chuob S, Pokharel M, Park JS (2011) Modeling and analysis of cloud computing availability based on eucalyptus platform for e-government data center. In: 2011 5th international conference on innovative mobile and internet services in ubiquitous computing (IMIS). IEEE, pp 289–296Google Scholar
  11. 11.
    Dantas J, Matos R, Araujo J, Maciel P (2012) An availability model for eucalyptus platform: an analysis of warm-standy replication mechanism. In: 2012 IEEE international conference on systems, man, and cybernetics (SMC). IEEE, pp 1664–1669Google Scholar
  12. 12.
    Dell (2012) Dell computers. http://www.dell.com/. Accessed 10 March 2014
  13. 13.
    DELL (2014) Datacenter capacity planner configuration. Dell. http://www.dell.com/html/us/products/rack_advisor_new/. Accessed 10 March 2014
  14. 14.
    Eucalyptus (2009) Eucalyptus open-source cloud computing infrastructure—an overview. Eucalyptus systems, GoletaGoogle Scholar
  15. 15.
    Eucalyptus (2014) Eucalyptus—the open source cloud platform. Eucalyptus systems. http://open.eucalyptus.com/. Accessed 5 March 2014
  16. 16.
    Heartbeat (2012) Linux-HA project. http://www.linux-ha.org. Accessed 5 March 2014
  17. 17.
    Heimann D, Mittal N, Trivedi K (1991) Dependability modeling for computer systems. In: Proceedings annual reliability and maintainability symposium, 1991. IEEE, Orlando, pp 120–128Google Scholar
  18. 18.
    Hong Z, Wang Y, Shi M (2012) Ctmc-based availability analysis of cluster system with multiple nodes. In: Advances in future computer and control systems. Springer, Berlin, pp 121–125Google Scholar
  19. 19.
    Hu T, Guo M, Guo S, Ozaki H, Zheng L, Ota K, Dong M (2010) Mttf of composite web services. In: 2010 international symposium on parallel and distributed processing with applications (ISPA). IEEE, pp 130–137Google Scholar
  20. 20.
    Johnson D, Murari K, Raju M, Suseendran RB, Girikumar Y (2010) Eucalyptus beginner’s guide, uec ednGoogle Scholar
  21. 21.
    Kim DS, Machida F, Trivedi KS (2009) Availability modeling and analysis of a virtualized system. In: 15th IEEE Pacific Rim international symposium on dependable computing, 2009. PRDC’09. IEEE, pp 365–371Google Scholar
  22. 22.
    Kuo W, Zuo MJ (2003) Optimal reliability modeling: principles and applications. Wiley, New YorkGoogle Scholar
  23. 23.
    Leangsuksun CB, Shen L, Liu T, Scott SL (2005) Achieving high availability and performance computing with an ha-oscar cluster. Future Gener Comput Syst 21(4):597–606CrossRefGoogle Scholar
  24. 24.
    Leangsuksun C, Shen L, Song H, Scott SL, Haddad31 I (2003) The modeling and dependability analysis of high availability oscar cluster system. In: High performance computing systems and applications. NRC Research Press, p 285Google Scholar
  25. 25.
    Liu T, Song H (2003) Dependability prediction of high availability oscar cluster server. In: Proceedings of the 2003 Int. Conf. on parallel and distributed processing techniques and applicationsGoogle Scholar
  26. 26.
    Maciel P, Trivedi K, Matias R, Kim D (2011) Performance and dependability in service computing: Concepts, techniques and research directions, ser. In: Premier Reference Source. Igi GlobalGoogle Scholar
  27. 27.
    Matos R, Maciel PRM, Machida F, Kim DS, Trivedi KS (2012) Sensitivity analysis of server virtualized system availability. IEEE Trans Reliab 61(4):994–1006CrossRefGoogle Scholar
  28. 28.
    O’Connor P, Kleyner A (2011) Practical reliability engineering. Wiley, New YorkGoogle Scholar
  29. 29.
    of Energy, U.D.: City of palo alto utilities—palo alto clean. Clean local energy acessible now (2013). http://energy.gov. Accessed 21 March 2014
  30. 30.
    Power S (2015) Laerence berkeley national laboratory. http://standby.lbl.gov/. Accessed 3 Feb 2015
  31. 31.
    Sathaye A, Ramani S, Trivedi KS (2000) Availability models in practice. In: Proc. of intl. workshop on fault-tolerant control and computing (FTCC-1)Google Scholar
  32. 32.
    Sun D, Chang G, Guo Q, Wang C, Wang X (2010) A dependability model to enhance security of cloud environment using system-level virtualization techniques. In: 2010 1st international conference on pervasive computing signal processing and applications (PCSPA). IEEE, pp 305–310Google Scholar
  33. 33.
    Wei B, Lin C, Kong X (2011) Dependability modeling and analysis for the virtual data center of cloud computing. In: 2011 IEEE 13th international conference on high performance computing and communications (HPCC). IEEE, pp 784–789Google Scholar
  34. 34.
    Yeow WL, Westphal C, Kozat UC (2010) A resilient architecture for automated fault tolerance in virtualized data centers. In: 2010 IEEE Network operations and management symposium (NOMS). IEEE, pp 866–869Google Scholar

Copyright information

© Springer-Verlag Wien 2015

Authors and Affiliations

  • Jamilson Dantas
    • 1
  • Rubens Matos
    • 1
  • Jean Araujo
    • 1
  • Paulo Maciel
    • 1
  1. 1.Informatics CenterFederal University of PernambucoRecifeBrazil

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