Model-Based Sensitivity of a Disaster Tolerant Active-Active GENESIS Cloud System

  • Tuan Anh Nguyen
  • Xuhua Rui
  • Damsub Lim
  • Jun Oh
  • Dugki MinEmail author
  • Eunmi Choi
  • Tran Duc Thang
  • Nguyen Nhu Son
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 221)


Modern cloud computing systems are prone to disasters. And the true cost due to service outages is reportedly huge. Some of previous works presented the use of hierarchical models: fault tree (FT), reliability block diagram (RBD) along with state-space models: continuous time Markov chain (CTMC) or stochastic petri nets (SPN) to assess the reliability/availability of cloud systems, but with much simplification. In this paper, we attempt to propose a combinatorial monolithic model using reliability graph (RG) for a real-world cloud system called general purpose integrated cloud system (GENESIS). The system is designed in active-active high availability configuration with two geographically distributed cloud sites for the sake of disaster tolerance (DT). We then present the model-based comprehensive analysis of system reliability/availability and their sensitivity. The results pinpoint different findings in which the architecture of active-active and geographically dispersed sites with appropriate interconnections of the cloud apparently enhance the system reliability/availability and assure disaster tolerance for the cloud.


Disaster tolerance High availability GENESIS Reliability graph 



– This research was supported by the Vietnam-Korea cooperation project: VAST.HTQT.HANQUOC.01/17-18 managed by Vietnam Academy of Science and Technology.

– This work was supported under the framework of international cooperation program managed by the National Research Foundation of Korea (project number, FY2016K2A9A1A06925440).


  1. 1.
    Nguyen, T.A., Kim, D.S., Park, J.S.: Availability modeling and analysis of a data center for disaster tolerance. Future Gener. Comput. Syst. (2015).
  2. 2.
    Ponemon Institute: Calculating the Cost of Data Center Outages (Report). Technical report (2013)Google Scholar
  3. 3.
    Miller, R.: Failure rates in google data centers (Report). Technical report, Data Center Knowledge (2008)Google Scholar
  4. 4.
    Gagnaire, M., Diaz, F., Coti, C., Cérin, C., Shiozaki, K., Xu, Y., Delort, P., Smets, J.-P., Lous, J.L., Lubiarz, S., Leclerc, P.: Downtime statistics of current cloud solutions. Technical report, The International Working Group on Cloud Computing Resiliency (2013)Google Scholar
  5. 5.
  6. 6.
  7. 7.
    Loveland, S., Dow, E.M., LeFevre, F., Beyer, D., Chan, P.F.: Leveraging virtualization to optimize high-availability system configurations. IBM Syst. J. 47(4), 591–604 (2008). CrossRefGoogle Scholar
  8. 8.
    Kim, D.S., Machida, F., Trivedi, K.S.: Availability modeling and analysis of a virtualized system. In: 2009 15th IEEE Pacific Rim International Symposium on Dependable Computing, vol. 1, pp. 365–371. IEEE, November 2009.
  9. 9.
    Nguyen, T.A., Kim, D.S., Park, J.S.: Availability modeling and analysis of a virtualized servers system (2014).
  10. 10.
    Nguyen, T.A., Min, D., Park, J.S.: A comprehensive sensitivity analysis of a data center network with server virtualization for business continuity. Math. Probl. Eng. 2015, 1–20 (2015). Google Scholar
  11. 11.
    Kim, D.S., Hong, J.B., Nguyen, T.A., Machida, F., Trivedi, K.S.: Availability modeling and analysis of a virtualized system using stochastic reward nets. In: Proceedings of 16th IEEE International Conference on Computer and Information Technology (IEEE CIT 2016). IEEE, Fiji (2016)Google Scholar
  12. 12.
    Machida, F., Kim, D.S., Trivedi, K.S.: Modeling and analysis of software rejuvenation in a server virtualized system with live VM migration. Perform. Eval. 70(3), 212–230 (2013)CrossRefGoogle Scholar
  13. 13.
    Trivedi, K.S., Kim, D.S., Ghosh, R.: System availability assessment using stochastic models. Appl. Stoch. Models Bus. Ind. 29(2), 94–109 (2013). MathSciNetCrossRefGoogle Scholar
  14. 14.
    Smith, W.E., Trivedi, K.S., Tomek, L.A., Ackaret, J.: Availability analysis of blade server systems. IBM Syst. J. 47(4), 621–640 (2008). CrossRefGoogle Scholar
  15. 15.
    Costa, I., Araujo, J., Dantas, J., Campos, E., Silva, F.A., Maciel, P.: Availability evaluation and sensitivity analysis of a mobile backend-as-a-service platform. Qual. Reliab. Eng. Int. (2015).
  16. 16.
    Matos, R., Dantas, J., Araujo, J., Trivedi, K.S., Maciel, P.: Redundant eucalyptus private clouds: availability modeling and sensitivity analysis. J. Grid Comput. 1–22 (2016).
  17. 17.
    Melo, M., Maciel, P., Araujo, J., Matos, R., Araujo, C.: Availability study on cloud computing environments: live migration as a rejuvenation mechanism. In: 2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), pp. 1–6. IEEE, June 2013.
  18. 18.
    Sousa, E., Silva, E., Lins, F., Tavares, E., Maciel, P.: Dependability evaluation of cloud infrastructures. In: 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 1282–1287. IEEE (2014).
  19. 19.
    Silva, B., Maciel, P.R.M., Zimmermann, A., Brilhante, J.: Survivability evaluation of disaster tolerant cloud computing systems. In: Proceedings of Probabilistic Safety Assessment and Management (PSAM12), p. 453, Hawaii, USA (2014).
  20. 20.
    Nguyen, T.A., Eom, T., An, S., Park, J.S., Hong, J.B., Kim, D.S.: Availability modeling and analysis for software defined networks. In: 2015 IEEE 21st Pacific Rim International Symposium on Dependable Computing (PRDC), April, pp. 159–168. IEEE, November 2015.
  21. 21.
    Radhakrishnan, R., Mark, K., Powell, B.: IT service management for high availability. IBM Syst. J. 47(4), 549–561 (2008). CrossRefGoogle Scholar
  22. 22.
    Morrill, H., Beard, M., Clitherow, D.: Achieving continuous availability of IBM systems infrastructures. IBM Syst. J. 47(4), 493–503 (2008). CrossRefGoogle Scholar
  23. 23.
    Lumpp, T., Schneider, J., Holtz, J., Mueller, M., Lenz, N., Biazetti, A., Petersen, D.: From high availability and disaster recovery to business continuity solutions. IBM Syst. J. 47(4), 605–619 (2008)CrossRefGoogle Scholar
  24. 24.
    Clitherow, D., Brookbanks, M., Clayton, N., Spear, G.: Combining high availability and disaster recovery solutions for critical IT environments. IBM Syst. J. 47(4), 563–575 (2008). CrossRefGoogle Scholar
  25. 25.
    Adeshiyan, T., Attanasio, C.R., Farr, E.M., Harper, R.E., Pelleg, D., Schulz, C., Spainhower, L.F., Ta-Shma, P., Tomek, L.A.: Using virtualization for high availability and disaster recovery. IBM J. Res. Dev. 53(4), 8:1–8:11 (2009). CrossRefGoogle Scholar
  26. 26.
    Silva, B., Maciel, P., Zimmermann, A.: Performability models for designing disaster tolerant Infrastructure-as-a-Service cloud computing systems. In: 8th International Conference for Internet Technology and Secured Transactions (ICITST-2013), pp. 647–652. Infonomics Society, December 2013.
  27. 27.
    Silva, B., Maciel, P., Tavares, E., Zimmermann, A.: Dependability models for designing disaster tolerant cloud computing systems. In: 2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), pp. 1–6. IEEE, June 2013.
  28. 28.
    Andrade, E., Nogueira, B., Matos, R., Callou, G., Maciel, P.: Availability modeling and analysis of a disaster-recovery-as-a-service solution. Computing 99, 1–26 (2017). MathSciNetCrossRefGoogle Scholar
  29. 29.
    Santana, G.A.A.: Data Center Virtualization Fundamentals: Understanding Techniques and Designs for Highly Efficient Data Centers with Cisco Nexus, UCS, MDS, and Beyond. Cisco Press, Indianapolis (2013)Google Scholar
  30. 30.
    Trivedi, K.S.: SHARPE 2002: symbolic hierarchical automated reliability and performance evaluator. In: Proceedings of the 2002 International Conference on Dependable Systems and Networks, p. 544. IEEE Computer Society (2002).
  31. 31.
    Trivedi, K.S., Sahner, R.: SHARPE at the age of twenty two. ACM SIGMETRICS Perform. Eval. Rev. 36(4), 52 (2009). CrossRefGoogle Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  • Tuan Anh Nguyen
    • 1
  • Xuhua Rui
    • 1
  • Damsub Lim
    • 1
  • Jun Oh
    • 1
  • Dugki Min
    • 1
    Email author
  • Eunmi Choi
    • 2
  • Tran Duc Thang
    • 3
  • Nguyen Nhu Son
    • 3
  1. 1.School of Computer Science and EngineeringKonkuk UniversitySeoulSouth Korea
  2. 2.School of Management Information SystemsKookmin UniversitySeoulSouth Korea
  3. 3.Institute of Information TechnologyVietnam Academy of Science and TechnologyHanoiVietnam

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