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Autonomous Migration of Virtual Machines to Reduce Energy Consumption of Servers

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Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS 2022)

Abstract

It is critical to reduce the electric energy consumption of information systems to realize green societies. In this paper, we take the live virtual machine migration approach to reducing the energy consumption of servers. In our previous studies, each server is assumed to be able to obtain the local state of every other server like the number of active processes and anytime accept any virtual machine from another server. In reality, each server cannot obtain the local state of another server without communicating with each other. In addition, a server cannot accept a virtual machine from another server if the server is overloaded. In this paper, we newly propose an AMVM (Asynchronous Migration of Virtual Machines) protocol to synchronize servers to decide on which server to make a virtual machine migrate to which server.

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References

  1. KVM: Main Page - KVM (Kernel Based Virtual Machine) (2015). http://www.linux-kvm.org/page/Mainx_Page

  2. Enokido, T., Aikebaier, A., Takizawa, M.: Process allocation algorithms for saving power consumption in peer-to-peer systems. IEEE Trans. Ind. Electron. 58(6), 2097–2105 (2011)

    Article  Google Scholar 

  3. Enokido, T., Aikebaier, A., Takizawa, M.: A model for reducing power consumption in peer-to-peer systems. IEEE Syst. J. 4(2), 221–229 (2010)

    Article  Google Scholar 

  4. Enokido, T., Aikebaier, A., Takizawa, M.: An extended simple power consumption model for selecting a server to perform computation type processes in digital ecosystems. IEEE Trans. Ind. Inform. 10(2), 1627–1636 (2014)

    Article  Google Scholar 

  5. Enokido, T., Takizawa, M.: Integrated power consumption model for distributed systems. IEEE Trans. Ind. Electron. 60(2), 824–836 (2013)

    Article  Google Scholar 

  6. Enokido, T., Duolikun, D., Takizawa, M.: The energy consumption laxity-based algorithm to perform computation processes in virtual machine environments. Int. J. Grid Util. Comput. 10(5), 545–555 (2019)

    Article  Google Scholar 

  7. Enokido, T., Duolikun, D., Takizawa, M.: The improved redundant active time-based (IRATB) algorithm for process replication. In: Barolli, L., Woungang, I., Enokido, T. (eds.) AINA 2021. LNNS, vol. 225, pp. 172–180. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-75100-5_16

    Chapter  Google Scholar 

  8. Enokido, T., Duolikun, D., Takizawa, M.: The improved redundant active time-based algorithm with forcing termination of meaningless replicas in virtual machine environments. In: Barolli, L., Chen, H.-C., Enokido, T. (eds.) NBiS 2021. LNNS, vol. 313, pp. 50–58. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-84913-9_5

    Chapter  Google Scholar 

  9. Kataoka, H., Duolikun, D., Sawada, A., Enokido, T., Takizawa, M.: Energy-aware server selection algorithms in a scalable cluster. In: Proceedings of the 30th International Conference on Advanced Information Networking and Applications, pp. 565–572 (2016)

    Google Scholar 

  10. Kataoka, H., Sawada, A., Dilawaer, D., Enokido, T., Takizawa, M.: Multi-level power consumption and computation models and energy-efficient server selection algorithms in a scalable cluster. In: Proceedings of the 19th International Conference on Network-Based Information Systems, pp. 210–217 (2016)

    Google Scholar 

  11. Kataoka, H., Nakamura, S., Duolikun, D., Enokido, T., Takizawa, M.: Multi-level power consumption model and energy-aware server selection algorithm. Int. J. Grid Util. Comput. 8(3), 201–210 (2017)

    Article  Google Scholar 

  12. Duolikun, D., Enokido, T., Takizawa, M.: Energy-efficient dynamic clusters of servers. In: Proceedings of the 8th International Conference on Broadband and Wireless Computing, Communication and Applications, pp. 253–260 (2013)

    Google Scholar 

  13. Duolikun, D., Enokido, T., Takizawa, M.: Static and dynamic group migration algorithms of virtual machines to reduce energy consumption of a server cluster. In: Nguyen, N.T., Kowalczyk, R., Xhafa, F. (eds.) Transactions on Computational Collective Intelligence XXXIII. LNCS, vol. 11610, pp. 144–166. Springer, Heidelberg (2019). https://doi.org/10.1007/978-3-662-59540-4_8

    Chapter  Google Scholar 

  14. Duolikun, D., Enokido, T., Takizawa, M.: Simple algorithms for selecting an energy-efficient server in a cluster of servers. Int. J. Commun. Netw. Distrib. Syst. 21(1), 1–25 (2018)

    Google Scholar 

  15. Duolikun, D., Watanabe, R., Enokido, T., Takizawa, M.; An eco migration algorithm of virtual machines in a server cluster. In: Proceedings of IEEE the 32nd International Conference on Advanced Information Networking and Applications, pp. 189–196 (2018)

    Google Scholar 

  16. Duolikun, D., Enokido, T., Takizawa, M.: Energy-efficient group migration of virtual machines in a cluster. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds.) AINA 2019. AISC, vol. 926, pp. 144–155. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-15032-7_12

    Chapter  Google Scholar 

  17. Duolikun, D., Enokido, T., Barolli, L., Takizawa, M.: A monotonically increasing (MI) algorithm to estimate energy consumption and execution time of processes on a server. In: Proceedings of the 24th International Conference on Network-Based Information Systems, pp. 1–12 (2021)

    Google Scholar 

  18. Duolikun, D., Enokido, T., Barolli, L., Takizawa, M.: An energy-efficient algorithm to make virtual machines migrate in a server cluster. In: Barolli, L. (ed.) BWCCA 2021. LNNS, vol. 346, pp. 25–36. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-90072-4_3

    Chapter  Google Scholar 

  19. Duolikun, D., Enokido, T., Barolli, L., Takizawa, M.: An energy-efficient algorithm to make virtual machines migrate in a server cluster. Accepted at Proceedings of the 10th International Conference on Emerging Internet, Data and Web Technologies, pp. 130–141 (2022)

    Google Scholar 

  20. Duolikun, D., Enokido, T., Barolli, L., Takizawa, M.: An energy consumption model of servers to make virtual machines migrate. In: Proceedings of the 33rd International Conference on Advanced Information Networking and Applications, pp. 24–36 (2022)

    Google Scholar 

  21. Noaki, N., Saito, T., Duolikun, D., Enokido, T., Takizawa, M.: An energy-efficient algorithm for virtual machines to migrate considering migration time. In: Barolli, L., Takizawa, M., Enokido, T., Chen, H.-C., Matsuo, K. (eds.) BWCCA 2020. LNNS, vol. 159, pp. 341–354. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-61108-8_34

    Chapter  Google Scholar 

  22. Noguchi, K., Saito, T., Duolikun, D., Enokido, T., Takizawa, T.: An algorithm to select a server to minimize the total energy consumption of a cluster. In: Proceedings of the 15th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, pp. 18–28 (2020)

    Google Scholar 

  23. Natural Resources Defense Council (NRDS): Data center efficiency assessment - scaling up energy efficiency across the data center industry: Evaluating key drivers and barriers (2014). http://www.nrdc.org/energy/files/data-center-efficiency-assessment-IP.pdf

  24. Watanabe, R., Duolikun, D., Takizawa, M.: Simple estimation and energy-aware migration models of virtual machines in a server cluster. Concurrency Comput. Pract. Exp. 30(21), e4771 (2018)

    Google Scholar 

  25. Oma, R., Nakamura, S., Duolikun, D., Enokido, T., Takizawa, M.: An energy-efficient model for fog computing in the Internet of Things (IoT). Internet Things 1–2, 14–26 (2018)

    Article  Google Scholar 

  26. Oma, R., Nakamura, S., Enokido, T., Takizawa, M.: A tree-based model of energy-efficient fog computing systems in IoT. In: Barolli, L., Javaid, N., Ikeda, M., Takizawa, M. (eds.) CISIS 2018. AISC, vol. 772, pp. 991–1001. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-93659-8_92

    Chapter  Google Scholar 

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Correspondence to Dilawaer Duolikun .

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Duolikun, D., Enokido, T., Barolli, L., Takizawa, M. (2022). Autonomous Migration of Virtual Machines to Reduce Energy Consumption of Servers. In: Barolli, L. (eds) Innovative Mobile and Internet Services in Ubiquitous Computing. IMIS 2022. Lecture Notes in Networks and Systems, vol 496. Springer, Cham. https://doi.org/10.1007/978-3-031-08819-3_3

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