VM\(^3\): Virtual Machine Multicast Migration Based on Comprehensive Load Forecasting

  • Feng GuoEmail author
  • Dong Zhang
  • Zhengwei Liu
  • Kaiyuan Qi
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 142)


Although Virtual Machine (VM) is a fundamental technique for Cloud Operation System (Cloud OS), lack of task model and dynamic usability evaluation are great challenges in VM migration. Hence, this paper proposes a VM multicast migration based on comprehensive load forecasting mechanism named VM\(^3\). In this paper, we design a VM placement algorithm based on comprehensive load forecasting, which provides an accurate selection of destination host according to the comprehensive network performance including bandwidth, latency, etc., while only the computing node offloading is considered in the tradition algorithms. Furthermore, we propose a multicast migration mechanism to reduce the computation before migration, and support parallel migration. Through implements and experiments it proves that VM\(^3\) improves the accuracy and efficiency of VM cluster migration, and it is practical and widely applicable.


Cloud operation system Virtual machine Multicast Placement algorithm Migration mechanism 


  1. 1.
    Vouk, M.A.: Cloud computing-issues, research and implementations. CIT J. Comput. Inform. Technol. 16(4), 235–246 (2008)Google Scholar
  2. 2.
    Barham, P., Dragovic, B., Fraser, K., Hand, S., Harris, T., Ho, A., Neugebauer, R., Pratt, I., Warfield, A.: Xen and the art of virtualization. ACM SIGOPS Oper. Syst. Rev. 37(5), 164–177 (2003)CrossRefGoogle Scholar
  3. 3.
    Lowe, S.: Mastering VMware vSphere 4. Wiley, Indianapolis (2009)Google Scholar
  4. 4.
    Williams, D.E.: Virtualization with Xen: Including XenEnterprise, XenServer, and XenExpress. Syngress (2007)Google Scholar
  5. 5.
    Menasce, D., Bennani, M.N.: Autonomic virtualized environments. In: 2006 International Conference on Autonomic and Autonomous Systems, ICAS 2006, p. 28. IEEE (2006)Google Scholar
  6. 6.
    Zhao, W., Wang, Z., Luo, Y.: Dynamic memory balancing for virtual machines. ACM SIGOPS Oper. Syst. Rev. 43(3), 37–47 (2009)CrossRefGoogle Scholar
  7. 7.
    Song, Y., Li, Y., Wang, H., Zhang, Y., Feng, B., Zang, H., Sun, Y.: A service-oriented priority-based resource scheduling scheme for virtualized utility computing. In: Sadayappan, P., Parashar, M., Badrinath, R., Prasanna, V.K. (eds.) HiPC 2008. LNCS, vol. 5374, pp. 220–231. Springer, Heidelberg (2008) CrossRefGoogle Scholar
  8. 8.
    Song, Y., Wang, H., Li, Y., Feng, B., Sun, Y.: Multi-tiered on-demand resource scheduling for vm-based data center. In: Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, pp. 148–155. IEEE Computer Society (2009)Google Scholar
  9. 9.
    Resource management with VMware DRS.
  10. 10.
    Hu, L., Jin, H., Liao, X., Xiong, X., Liu, H.: Magnet: a novel scheduling policy for power reduction in cluster with virtual machines. In: 2008 IEEE International Conference on Cluster Computing, pp. 13–22. IEEE (2008)Google Scholar
  11. 11.
    Angiuoli, S.V., Matalka, M., Gussman, A., Galens, K., Vangala, M., Riley, D.R., Arze, C., White, J.R., White, O., Fricke, W.F.: Clovr: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing. BMC Bioinform. 12(1), 356 (2011)CrossRefGoogle Scholar
  12. 12.
    Lagar-Cavilla, H.A., Whitney, J.A., Scannell, A.M., Patchin, P., Rumble, S.M., De Lara, E., Brudno, M., Satyanarayanan, M.: Snowflock: rapid virtual machine cloning for cloud computing. In: Proceedings of the 4th ACM European Conference on Computer Systems, pp. 1–12. ACM (2009)Google Scholar

Copyright information

© Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2015

Authors and Affiliations

  • Feng Guo
    • 1
    Email author
  • Dong Zhang
    • 1
  • Zhengwei Liu
    • 1
  • Kaiyuan Qi
    • 1
  1. 1.State Key Laboratory of High-end Server and Storage TechnologySystem Soft Department of InspurJinanChina

Personalised recommendations