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Soft Computing and Signal Processing pp 233–241Cite as

Effects of Different Queueing Models on Migration of Virtual Machines

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 898))

Abstract

Virtualization is an act of creating virtual resources that are made accessible by the application of cloud computing. In case of failure of a virtual machine, it is imperative to shift the processes running on this machine to another. This activity is known as live virtual machine migration and is classified under the major issues of research. Xia (2015) proposed a mathematical model to analyze this problem in which the work has been done in two phases. It is showing a state transition model system in which the M/M/1/K model has been utilized in phase1 to find the rejection probability of the jobs in the phase2. Each virtual machine is considered to have a buffer to store the incoming buffer. The major issue being discussed in this paper is the relation of the rejection probability of jobs with the changing size of the buffer. It actually provides an exhaustive analysis of three different queueing models, i.e., M/M/1/∞, M/M/∞, and M/M/1/K. The simulations are carried out in MATLAB, and the results are analyzed based on the rejection probability of the jobs. It is observed that with an increase in the request arrival rate, the rejection probability of jobs increases. However, with an increase in execution rate, the rejection probability of jobs decreases. If we change the model to M/M/∞, actually, the formulas of request rejection probability and job rejection probability got changed that resulted in a continuous decrease in values of rejection rate lines as compared to the values of the author. Hence, we can say that changing the queueing model is beneficial.

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References

  1. Xia, Y., Zhou, M., Luo, X., Zhu, Q., Li, J., Huang, Y.: Stochastic modeling and quality evaluation of infrastructure-as-a-service clouds. IEEE Trans. Autom. Sci. Eng. 162–170 (2015)

    Article  Google Scholar 

  2. Sahoo, J., Mohapatra, S., Lath, R.: Virtualization: a survey on concepts, taxonomy and associated security issues. In: 2010 2nd International Conference on Computer and Network Technology (ICCNT), pp. 222–226. IEEE (2010)

    Google Scholar 

  3. Strunk, A.: Costs of virtual machine live migration: a survey. In: 2012 IEEE 8th World Congress on Services (SERVICES), pp. 323–329. IEEE (2012)

    Google Scholar 

  4. Loganayagi, B., Sujatha, S.: Enhanced cloud security by combining virtualization and policy monitoring techniques. Procedia Eng. 30, 654–661 (2012)

    Article  Google Scholar 

  5. Chen, H.P., Li, S.C.: A queueing based model for performance management on cloud. In: International Conference on Advanced Information Management and Service (IMS), pp. 83–88. IEEE (2011)

    Google Scholar 

  6. Anala, M.R., Shetty, J., Shobha, G.: A framework for secure live migration of virtual machines. In: 2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 243–248. IEEE (2013)

    Google Scholar 

  7. Baghshahi, S.S., Jabbehdari, S., Adabi, S.: Virtual machine migration based on Greedy algorithm in cloud computing. Int. J. Comput. Appl. 96(12) (2014)

    Google Scholar 

  8. Cao, J., Andersson, M., Nyberg, C., Kihl, M.: Web server performance modeling using an M/G/1/K*PS queue. In: 10th International Conference on Telecommunications, 2003. ICT 2003, vol. 2, pp. 1501–1506. IEEE (2003)

    Google Scholar 

  9. Xiong, K., Perros, H.: Service performance and analysis in cloud computing. In: Services-I, 2009 World Conference, pp. 693–700. IEEE (2009)

    Google Scholar 

  10. Dai, Y.S., Yang, B., Dongarra, J., Zhang, G.: Cloud service reliability: modeling and analysis. In: 15th IEEE Pacific Rim International Symposium on Dependable Computing, pp. 1–17. IEEE (2009)

    Google Scholar 

  11. Yang, B., Tan, F., Dai, Y. S., Guo, S.: Performance evaluation of cloud service considering fault recovery. In: IEEE International Conference on Cloud Computing, pp. 571–576. Springer, Berlin, Heidelberg (2009)

    Google Scholar 

  12. He, S., Guo, L., Ghanem, M., Guo, Y.: Improving resource utilisation in the cloud environment using multivariate probabilistic models. In: 2012 IEEE 5th International Conference Cloud Computing(CLOUD), pp. 574–581. IEEE (2012)

    Google Scholar 

  13. Ghosh, R., Trivedi, K.S., Naik, V.K., Kim, D.S.: End-to-end performability analysis for infrastructure-as-a-service cloud: an interacting stochastic models approach. In: 2010 IEEE 16th Pacific Rim International Symposium on Dependable Computing (PRDC), pp. 125–132. IEEE (2010)

    Google Scholar 

  14. Li, B., Li, J., Huai, J., Wo, T., Li, Q., Zhong, L.: Ena cloud: an energy saving application live placement approach for cloud computing environments. IEEE (2009)

    Google Scholar 

  15. Karlapudi, H.: Web application performance prediction. In: Proceedings of International Conference on Communication and Computer Networks, IASTED, pp. 281–286 (2004)

    Google Scholar 

  16. Mastelic, T., Brandic, I.: Recent trends in energy efficient cloud computing. J. Latex 11(4) (2012)

    Google Scholar 

  17. Sarker, T.K., Tang, M.: Performance-driven live migration of multiple virtual machines in datacenters. In: International Conference on Granular Computing (GrC), pp. 253–258. IEEE (2013)

    Google Scholar 

  18. Chanchio, K., Thaenkaew, P.: Time-bound, thread-based live migration of virtual machines. In: 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), 2014, pp. 364–373. IEEE (2014)

    Google Scholar 

  19. Zheng, J., Ng, T.E., Sripanidkulchai, K., Liu, Z.: Pacer: a progress management system for live virtual machine migration. IEEE Trans. Cloud Comput. 10(4), 369–382 (2013)

    Google Scholar 

  20. Vilaplana, J., Solsona, F., Teixidó, I., Mateo, J., Abella, F., Rius, J.: A queueing theory model for cloud computing. J. Supercomput. 492–507 (2014)

    Article  Google Scholar 

  21. Pham, C., Hong, C.S.: Using queueing model to analyse the live migration process in data centers, pp. 1136–1138. IEEE (2014)

    Google Scholar 

  22. Yu, L., Chen, L., Cai, Z., Shen, H., Liang, Y., Pan, Y.: Stochastic load balancing for virtual resource management in datacenters. IEEE Trans. Cloud Comput. IEEE (2014)

    Google Scholar 

  23. Kumar, N., Saxena, S.: Migration performance of cloud applications—a quantitative analysis. Procedia Comput. Sci. 45, 823–831 (2015)

    Article  Google Scholar 

  24. Sandhya, S., Revathi, S., NK, C.: Performance analysis and comparative analysis of process migration using genetic algorithm. Int. J. Sci. Eng. Technol. Res. 5(11) (2016)

    Google Scholar 

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Authors and Affiliations

  1. K. R. Mangalam University, Gurugram, Haryana, India

    Surabhi Sachdeva & Neeraj Gupta

Authors
  1. Surabhi Sachdeva
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  2. Neeraj Gupta
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Correspondence to Surabhi Sachdeva .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Software Engineering, Monmouth University, West Long Branch, NJ, USA

    Jiacun Wang

  2. Department of Information Technology, National Institute of Technology Karnataka, Surathkal, Mangaluru, Karnataka, India

    G. Ram Mohana Reddy

  3. Department of Computer Science and Engineering, JNTUH College of Engineering Hyderabad, Hyderabad, Telangana, India

    V. Kamakshi Prasad

  4. Department of Electronics and Communication Engineering, Malla Reddy College of Engineering & Technology, Secunderabad, Telangana, India

    V. Sivakumar Reddy

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Sachdeva, S., Gupta, N. (2019). Effects of Different Queueing Models on Migration of Virtual Machines. In: Wang, J., Reddy, G., Prasad, V., Reddy, V. (eds) Soft Computing and Signal Processing . Advances in Intelligent Systems and Computing, vol 898. Springer, Singapore. https://doi.org/10.1007/978-981-13-3393-4_24

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