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Adaptive Live Task Migration in Cloud Environment for Significant Disaster Prevention and Cost Reduction

  • Namra Bhadreshkumar Shah
  • Tirth Chetankumar Thakkar
  • Shrey Manish Raval
  • Harshal Trivedi
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 106)

Abstract

The “Cloud” in IT terms is straightforwardly a storage of data. Cloud computing is one of the most emerging technologies in IT industries as of late and it means to store and manage data persistently over the cloud (the Internet) at a very low cost. Migration to and among cloud servers helps IT professionals to protect their data, prevent them from any disasters, and provide their resources efficiently without any delay or problems. Auto-scaling provides agility in managing virtual machines, whether to increase or decrease them. Any successful prevention of disaster will necessarily depend on the migration of certain tasks from one virtual machine to another. Most of the data recovery approaches suffer from high recovery time, balancing load and to cut cost. In this work, we incorporated an adaptive live task migration technique to prevent as many disasters as possible and to significantly reduce cost which is presented in the form of a graph later in the performance evaluation section. The experimental outcome shows that the proposed algorithm outperforms other approaches by 15–25% in terms of reducing cost, and balancing the load among available nodes. It also diminishes any prospect of disaster.

Keywords

Cloud computing Live migration Adaptive task migration Disaster prevention Cost reduction Auto-scaling 

References

  1. 1.
    Reese, G.: Cloud Application Architectures: Building Applications and Infrastructure. The Cloud: O’Reilly MediaGoogle Scholar
  2. 2.
    Mell, P., Grance, T.: The NIST definition of cloud computing. In: National Institute of Standards and Technology, vol 53, pp. 1–50 NIST, Gaithersburg (2011)Google Scholar
  3. 3.
    Moharana, S.S., Ramesh, R.D., Powar, D.: Analysis of load balancers in cloud computing. Int. J. Comput. Sci. Eng. (IASET) 2, 101–108 (2013)Google Scholar
  4. 4.
    Ahmad, R.W., Gani, A., Ab Hamid, S.H., Shiraz, M., Yousafzai, A., Xia, F.: A Survey on virtual Machines migration and server consolidation frameworks for cloud data centers. J. Netw. Comput. Appl. 52, 11–25 (2015)Google Scholar
  5. 5.
    Jamshidi, P., Ahmad, A., Pahl, C.: Cloud migration research: a systematic review. IEEE Trans. Cloud Comput. 1(2), 142–157 (2013)Google Scholar
  6. 6.
    Foster, I., Zhao, Y., Raicu, I., Lu, S.: Cloud computing and grid computing 360-degree compared. In: Proceedings of the Grid Computing Environments Workshop, pp: 99–106. IJSTR (2008)Google Scholar
  7. 7.
    Tang, Z., Mo, Y., Li, K.: Dynamic forecast scheduling algorithm for virtual machine placement in cloud computing environment. J. Super-Comput. 70(3), 1279–1296 (2014)CrossRefGoogle Scholar
  8. 8.
    Forsman, M., Glad, A., Lundberg, L., Ilie, D.: Algorithms for automated live migration of virtual machines. J. Syst. Softw. 101, 110–126 (2015). ISSN: 0164-1212Google Scholar
  9. 9.
    Michael, R.H., Umesh, D., Kartik, G.: Post-copy live migration of virtual machines. SIGOPS Oper. Syst. Rev. 43, 14–26 (2009)CrossRefGoogle Scholar
  10. 10.
    Chen, J., Qin, Y., Ye, Y., Tang, Z.: A live migration algorithm for virtual machine in a cloud computing environment. In: 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing and 2015 IEEE 12th International Conference on Autonomic and Trusted Computing and 2015 IEEE 15th International Conference on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom), Beijing, pp. 1319–1326 (2015)Google Scholar
  11. 11.
    Reeba, P.J., Shaji, R.S., Jayan, J.P.: A secure virtual machine migration using processor workload prediction method for cloud environment. In: 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT), Nagercoil, pp. 1–6 (2016)Google Scholar
  12. 12.
    Akram, S., Ghaleb, S., Ba, S., Siva, V.: Survey study of virtual machine migration techniques in cloud computing. Int. J. Comput. Appl. 177, 18–22 (2017)Google Scholar
  13. 13.
    Weining, L., Tao, F.: Live migration of virtual machine based on recovering system and CPU scheduling. In: 6th IEEE Joint International Information Technology and Artificial Intelligence Conference, Piscataway, NJ, USA, pp. 303–307, May 2009Google Scholar
  14. 14.
    Hai, J., Li, D., Song, W., Xuanhua, S., Xiaodong, P.: Live virtual machine migration with adaptive, memory compression. In: IEEE International Conference on Cluster Computing and Workshops, CLUSTER’09, pp. 1–10Google Scholar
  15. 15.
    Cloud computing architecture and its vulnerabilities. https://www.slideshare.net/VinayDwivedi3/cloud-computing-architecture-and-vulnerabilies. Accessed 13 Oct 2017
  16. 16.
    Kumar, A., Mishra, S., Mishra, A.: Priority with adoptive data migration in case of disaster using cloud computing use style. In: 2015 International Conference on Communication, Information and Computing Technology (ICCICT), Mumbai, pp. 1–6 (2015)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Namra Bhadreshkumar Shah
    • 1
  • Tirth Chetankumar Thakkar
    • 1
  • Shrey Manish Raval
    • 2
  • Harshal Trivedi
    • 3
  1. 1.Department of Computer EngineeringVishwakarma Government Engineering CollegeChandkheda, AhmedabadIndia
  2. 2.Silver Oak College of Engineering & TechnologyAhmedabadIndia
  3. 3.SoftVanAhmedabadIndia

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