Computing

, Volume 100, Issue 6, pp 621–644 | Cite as

A hierarchical approach for availability and performance analysis of private cloud storage services

Article
  • 87 Downloads

Abstract

Cloud computing brings new technologies and concepts that support communication services and data storage. Services like OneDrive, Google Drive and DropBox increase data availability and provide new features as synchronization and collaboration. These services require high availability and performance characteristics like high throughput and low probability that a timeout occurs, since it is fundamental to guarantee both business continuity and uninterrupted public services. In this research, we aim at evaluating availability and performance-related metrics for private cloud storage services. A hierarchical model-based strategy is proposed to evaluate distinct metrics by means of the composition of continuous-time Markov chains, reliability block diagrams and stochastic Petri nets. A case study is presented to illustrate the applicability of the proposed models through a cloud storage service hosted in the Eucalyptus platform. We also adopt availability importance index to identify the most critical components in relation to the system availability. Our numerical analyses indicate that, for instance, the adoption of redundant components reduces the probability that timeouts occur and the probability that users are attended due to failures. Furthermore, the results obtained from the stochastic models show that the proposed approach is indeed a good approximation to the measures obtained from the experiments conducted in a real cloud environment.

Keywords

Availability Performance RBD CTMC SPN Cloud storage 

Mathematics Subject Classification

68U20 65C40 

Notes

Acknowledgements

The authors would like to thank the FACEPE and CNPq for the financial support of this research.

References

  1. 1.
  2. 2.
    Bell K (2015) Google Drive is back online after brief outage. Marsable. http://mashable.com/2015/10/09/google-docs-sheets-down/
  3. 3.
    Fiveash K (2015) AWS outage knocks Amazon, Netflix, Tinder and IMDb in MEGA data collapse. The Register. http://www.theregister.co.uk/2015/09/20/aws-database-outage/
  4. 4.
    Xiong K, Perros H (2009) Service performance and analysis in cloud computing. In: 2009 Congress on services-I. IEEE, pp 693–700Google Scholar
  5. 5.
    Mell P, Grance T (2011) The NIST definition of cloud computingGoogle Scholar
  6. 6.
    Chung H, Park J, Lee S, Kang C (2012) Digital forensic investigation of cloud storage services. Digit Investig 9(2):81–95CrossRefGoogle Scholar
  7. 7.
    Enterprise HP (2015) Hpe helion eucalyptus. http://www8.hp.com/us/en/cloud/helion-eucalyptus-overview.html
  8. 8.
    Enterprise HP (2015) Eucalyptus documentation. http://docs.hpcloud.com/eucalyptus/4.2.1
  9. 9.
    Murata T (1989) Petri nets: properties, analysis and applications. Proc IEEE 77(4):541–580CrossRefGoogle Scholar
  10. 10.
    Trivedi K S (2008) Probability and statistics with reliability, queuing and computer science applications. Wiley, New YorkMATHGoogle Scholar
  11. 11.
    Maciel P, Trivedi K, Matias R, Kim D (2010) Dependability modeling. In: Performance and dependability in service computing: concepts, techniques and research directions. IGI Global, Hershey, Pennsylvania, USAGoogle Scholar
  12. 12.
    Ebeling CE (2004) An introduction to reliability and maintainability engineering. Tata McGraw-Hill Education, New YorkGoogle Scholar
  13. 13.
    Kuo W, Zhu X (2012) Importance measures in reliability, risk, and optimization: principles and applications. Wiley, New YorkCrossRefGoogle Scholar
  14. 14.
    Sigman K (1990) The stability of open queueing networks. Stoch Process Appl 35(1):11–25MathSciNetCrossRefMATHGoogle Scholar
  15. 15.
    Barabady J, Kumar U (2007) Availability allocation through importance measures. Int J Qual Reliab Manag 24(6):643–657CrossRefGoogle Scholar
  16. 16.
    Sas A (2015) Pydio—put your data in orbit. https://pydio.com/
  17. 17.
    Silva B, Matos R, Callou G, Figueiredo J, Oliveira D, Ferreira J, Dantas J, Lobo A, Alves V, Maciel P (2015) Mercury: an integrated environment for performance and dependability evaluation of general systems. In: Proceedings DSN-2015 Rio de Janeiro, RJ, BrazilGoogle Scholar
  18. 18.
    Foundation A (2016) Apache http server benchmarking tool. https://httpd.apache.org/docs/2.4/programs/ab.html
  19. 19.
    Halili EH (2008) Apache JMeter: a practical beginner’s guide to automated testing and performance measurement for your websites. Packt Publishing Ltd, BirminghamGoogle Scholar
  20. 20.
    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
  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, PRDC’09. IEEE, pp 365–371Google Scholar
  22. 22.
    Matos R, Andrade EC, Maciel P (2014) Evaluation of a disaster recovery solution through fault injection experiments. In: 2014 IEEE international conference on systems, man and cybernetics (SMC). IEEE, pp 2675–2680Google Scholar
  23. 23.
    Araujo J, Maciel P, Torquato M, Callou G, Andrade E (2014) Availability evaluation of digital library cloud services. In: 2014 44th Annual IEEE/IFIP international conference on dependable systems and networks (DSN). IEEE, pp 666–671Google Scholar
  24. 24.
    Matos R, Maciel PR, Machida F, Kim DS, Trivedi KS (2012) Sensitivity analysis of server virtualized system availability. IEEE Trans Reliab 61(4):994–1006CrossRefGoogle Scholar
  25. 25.
    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
  26. 26.
    Haung K, Ma Z, Sun L (2012) Performance evaluation of node in cloud storage. In: 2012 2nd International conference on consumer electronics, communications and networks (CECNet). IEEE, pp 2739–2744Google Scholar
  27. 27.
    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 Fifth international conference on innovative mobile and internet services in ubiquitous computing (IMIS). IEEE, pp 289–296Google Scholar
  28. 28.
    Ghosh R, Longo F, Frattini F, Russo S, Trivedi KS (2014) Scalable analytics for IaaS cloud availability. IEEE Trans Cloud Comput 2(1):57–70CrossRefGoogle Scholar
  29. 29.
    Sheng Y, Liu J, Shidong Z, Liang D (2013) Research and application of private cloud storage platform in high schools based on seafile. In: 2013 6th International conference on intelligent networks and intelligent systems (ICINIS). IEEE, pp 25–28Google Scholar
  30. 30.
    Hildmann T, Kao O (2014) Deploying and extending on-premise cloud storage based on owncloud. In: 2014 IEEE 34th international conference on distributed computing systems workshops (ICDCSW). IEEE, pp 76–81Google Scholar

Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Federal Institute of Education, Science, and Technology of Pernambuco (IFPE)Belo JardimBrazil
  2. 2.Department of Statistics and InformaticsFederal Rural University of Pernambuco (UFRPE)RecifeBrazil

Personalised recommendations