Journal of Network and Systems Management

, Volume 20, Issue 4, pp 579–600 | Cite as

Efficient Diagnosis Protocol to Enhance the Reliability of a Cloud Computing Environment

  • Mao-Lun Chiang


Cloud computing is attractive for users having more demands on the Internet services because it can provide a variety of services. It can provide a large number of applications on the Internet. However, the fault-tolerance of a cloud computing environment is a crucial challenge. One of the important issues surrounding fault-tolerance is the Byzantine Agreement (BA) problem. It requires a set of healthy processors to reach an agreement, even if some components are faulty. In general, the traditional BA protocol needs ⌊(n − 1)/3⌋ + 2 rounds to reach an agreement and detect faulty processors. This is unreasonable and inefficient in a cloud computing environment. Therefore, the FCA (Fast Cloud Agreement) protocol is proposed to enhance the reliability of the cloud computing environment in this paper. The FCA can reach an agreement and detect faulty processors by using a minimum number of messages simultaneously and efficiently. Besides, the maximum number of faulty processors can be detected by the FCA in a cloud computing environment.


Cloud computing Byzantine agreement Fault diagnosis agreement Fault-tolerance Reliability 



This work was supported in part by the Taiwan National Science Council under Grant NSC99-2221-E-324-041-MY3.


  1. 1.
    Halsall, F.: Data communications, computer networks and open systems, 4th edn. Addison-Wesley Publishers, Massachusetts (1995)Google Scholar
  2. 2.
    Vaquero, L.M., Merino, L.R., Caceres, J., Lindner, M.: A break in the clouds: towards a cloud definition. ACM SIGCOMM Comput. Commun. Rev. 39, 50–55 (2009)CrossRefGoogle Scholar
  3. 3.
    Gong, C., Liu, J., Zhang, Q., Chen, H., Gong, Z.: The characteristics of cloud computing. Proceedings of the International Conference on Parallel Processing, 275–279 (2010)Google Scholar
  4. 4.
    Zhang, S., Chen, X., Huo, X.: Cloud computing research and development trend. Proceedings of Second International Conference on Future Networks, 93–97 (2010)Google Scholar
  5. 5.
    Amazon Elastic Compute Cloud [URL]. Accessed 26 Oct 2009
  6. 6.
    Amazon Web Services. (2009). Accessed 26 July 2009
  7. 7.
    Gartner Says Cloud Computing Will Be As Influential As E-business. (2009). Accessed 26 July 2009
  8. 8.
    Google, Google app Engine. (2011). Accessed 20 July 2011
  9. 9.
    IBM Blue Cloud project [URL]. Accessed 20 Oct 2009
  10. 10.
    Microsoft, Windows Azure. (2009) Accessed 20 Oct 2009
  11. 11., What is cloud Computing? (2011). Accessed 20 July 2011
  12. 12.
    Zeus (2009). Accessed 20 Oct 2009
  13. 13.
    Bar-Noy, A., Dolev, D., Dwork, C., Raymond Strong, H.: Shifting gears: changing algorithms on the fly to expedite byzantine agreement. Inf. Comput. 97, 205–233 (1992)MATHCrossRefGoogle Scholar
  14. 14.
    Dolev, D., Reischuk, R.: Bounds on information exchange for byzantine agreement. J. ACM 32, 191–204 (1985)MathSciNetMATHCrossRefGoogle Scholar
  15. 15.
    Hsiao, H.S., Chin, Y.H., Yang, W.P.: Reaching fault diagnosis agreement under a hybrid fault model. IEEE Trans. Comput. 49, 980–986 (2000)Google Scholar
  16. 16.
    Meyer, F.J., Pradhan, D.K.: Consensus with dual failure modes. IEEE Trans. Parall. Distrib. Syst. 2, 214–222 (1991)CrossRefGoogle Scholar
  17. 17.
    Wang, S.S., Wang, S.C., Yan, K.Q.: An optimal solution for byzantine agreement under a hierarchical cluster-oriented mobile ad-hoc network. Comput. Electr. Eng. 36, 100–113 (2010)MathSciNetMATHCrossRefGoogle Scholar
  18. 18.
    Wang, S.C., Yan, K.Q., Wang, S.S., Zheng, G.Y.: Reaching agreement among virtual subnets in hybrid failure mode. IEEE Trans. Parallel Distrib. Syst. 19, 1–11 (2008)CrossRefGoogle Scholar
  19. 19.
    Yan, K.Q., Wang, S.S., Wang, S.C.: Reaching an agreement under wormhole networks within dual failure component. Int. J. Innov. Comput. Inform. Control 6, 1151–1164 (2010)Google Scholar
  20. 20.
    Fischer, M.J., Lynch, N.A.: A lower bound for the time to assure interactive consistency. Inform. Process. Lett. 14, 183–186 (1982)MathSciNetMATHCrossRefGoogle Scholar
  21. 21.
    Youtube (2011). Accessed 20 July 2011
  22. 22.
    Yan, K.Q., Wang, S.C.: grouping byzantine agreement. Comput. Stand. Interfaces 28, 75–92 (2005)CrossRefGoogle Scholar
  23. 23.
    Yan, K.Q., Wang, S.C.: Reaching fault diagnosis agreement on an unreliable general network. Inf. Sci. 170, 397–407 (2005)MathSciNetCrossRefGoogle Scholar
  24. 24.
    Lamport, L., Shostak, R., Pease, M.: The byzantine general’s problem. ACM Trans. Program. Lang. Syst. 4, 382–401 (1982)MATHCrossRefGoogle Scholar
  25. 25.
    Shin, K., Ramanathan, P.: Diagnosis of processors with byzantine faults in a distributed computing system. Proceedings of the Symposium Fault-tolerant Computing, 55–60 (1987)Google Scholar
  26. 26.
    Siu, H.S., Chin, Y.H., Yang, W.P.: A note on consensus on dual failure modes. IEEE Trans. Parallel Distrib. Syst. 7, 225–229 (1996)CrossRefGoogle Scholar
  27. 27.
    Deo, N.: Graph Theory with Applications to Engineering and Computer Science. N. J. Prentice Hall, Englewood Cliffs (1974)MATHGoogle Scholar
  28. 28.
    Krings, A.W., Fisher, T.: The byzantine agreement problem: optimal early stopping. Proceedings of 32nd Hawaii International Conference on System Sciences, LNCS 520, Springer, Berlin, 1–12 (1999)Google Scholar
  29. 29.
    Chiang, M.L.: Eventually byzantine agreement on CDS-based mobile ad hoc network. Ad Hoc Netw. 10, 388–400 (2012)CrossRefGoogle Scholar
  30. 30.
    Siu, H.S., Chin, Y.H., Yang, W.P.: Byzantine agreement in the presence of mixed faults on processors and links. IEEE Trans. Parallel Distrib. Syst. 9, 335–345 (1998)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Department of Information and Communication EngineeringChaoyang University of TechnologyTaichung CountyRepublic of China

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