Skip to main content

QoS-Aware Dynamical Resource Scheduling in Cloud Data Centers

  • Conference paper
  • First Online:
Security, Privacy, and Anonymity in Computation, Communication, and Storage (SpaCCS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12383))

  • 1060 Accesses

Abstract

In order to improve the utilization rate of cloud computing resources within the data center, the scheduler dynamically allocates resources according to the load of each node and migrates virtual machines. Virtual machine migration is one of the effective ways to realize the dynamic allocation of resources, and virtual machine migration will cause a certain quality of service interference to the services carried on it. We analyze the impact of virtual machine migration on service quality, study the problems of virtual machine migration timing, migration objects and migration destination, targeted optimization strategies, established an evaluation model of the impact of migration mechanism on service quality. Based on this, an effective dynamic resource scheduling strategy is proposed. Experimental results show that compared with the existing online migration strategy, our model can reduce unnecessary migration by about 33% on average while reducing migration costs by 30%. In addition, our proposed resource scheduling strategy solves the problem of insufficient resources during the subsequent migration of a heavily loaded virtual machine.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Shen, J., Zhou, T., Chen, X., Li, J., Susilo, W.: Anonymous and traceable group data sharing in cloud computing. IEEE Trans. Inf. Forensics Secur. 13(4), 912–925 (2018)

    Article  Google Scholar 

  2. Ling, L., Xiaozhen, M., Yulan, H.: CDN cloud: a novel scheme for combining CDN and cloud computing. In: 5th International Conference on Modelling, Identification and Control, vol. 01, pp. 687–690 (2013)

    Google Scholar 

  3. Ma, K., Yang, B.: Live data replication approach from relational tables to schema-free collections using stream processing framework. In: 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, pp. 26–31 (2015)

    Google Scholar 

  4. Pagani, S., Shafique, M., Khdr, H., Chen, J.-J., Henkel, J.: seBoost: selective boosting for heterogeneous manycores. In: Hardware/Software Codesign and System Synthesis, pp. 104–113 (2019)

    Google Scholar 

  5. Jianhong, M., Bangbang, R.: Strategies of controller selection balance for cloud data center network. Command Inf. Syst. Technol. 10(4), 96–100 (2017)

    Google Scholar 

  6. Mizusawa, N., Kon, J., Seki, Y., Tao, J., Yamaguchi, S.: Performance improvement of file operations on OverlayFS for containers. In: IEEE International Conference on Smart Computing, pp. 297–302 (2018)

    Google Scholar 

  7. Li, B., Zhang, W., Gu, X., Cong, L.: Research on the production scheduling for automobile parts based on hybrid algorithm. In: 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, vol. 2, pp. 267–270 (2013)

    Google Scholar 

  8. Wendi, C., Shaojie, M., Ran, D.: Generation and deployment technology for cloud simulation test environment. Command Inf. Syst. Technol. 10(3), 37–40 (2019)

    Google Scholar 

  9. Wu, X., Deng, S.: Research on optimizing strategy of database-oriented GIS graph database query. In: IEEE International Conference on Cloud Computing and Intelligence Systems, pp. 305–309 (2018)

    Google Scholar 

  10. Jangra, A., Kumar, A.: Dynamic prioritization based efficient task scheduling for grid computing. In: 2nd International Conference on Information Management in the Knowledge Economy, pp. 150–155 (2013)

    Google Scholar 

  11. Zhang, L., Han, T., Ansari, N.: Renewable energy-aware inter-datacenter virtual machine migration over elastic optical networks. In: IEEE 7th International Conference on Cloud Computing Technology and Science, pp. 440–443 (2015)

    Google Scholar 

  12. Li, Z.: Time synchronization method for cloud computing server clusters. Command Inf. Syst. Technol. 9(4), 63–67 (2017)

    Google Scholar 

  13. Filho, M.C.S., Monteiro, C.C., Inácio, P.R.M., Freire, M.M.: Approaches for optimizing virtual machine placement and migration in cloud environments: a survey. J. Parallel Distrib. Comput. 111, 222 (2018)

    Google Scholar 

  14. Heikkilä, M., Rättyä, A., Pieskä, S., Joni Jämsä, J.: Security challenges in small- and medium-sized manufacturing enterprises. In: 3rd International Symposium on Small-scale Intelligent Manufacturing Systems, pp. 25–30 (2020)

    Google Scholar 

  15. Aldahari, E.: Dynamic voltage and frequency scaling enhanced task scheduling technologies toward green cloud computing. In: International Conference on Computational Science and Intelligence, pp. 20–25 (2016)

    Google Scholar 

  16. Bożejko, W., Chaczko, Z., Nadybski, P., Wodecki, M.: Contemporary Complex Systems and Their Dependability 761, 74 (2018)

    Google Scholar 

  17. Lv, L., Liang, Q.: Communication-aware container placement and reassignment in large-scale internet data centers. IEEE J. Sel. Areas Commun. 37(3), 540–555 (2019)

    Google Scholar 

  18. Zhao, H., Wang, Q.: VM performance maximization and PM load balancing virtual machine placement in cloud. In: 2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, pp. 857–864 (2020)

    Google Scholar 

Download references

Acknowledgments

This work is supported in part by the National Key R&D Program of China under Grant 2019YFB2102002, in part by the National Natural Science Foundation of China under Grant 61802182.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xin Li .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Wu, K., Wang, L., Li, H., Li, X. (2021). QoS-Aware Dynamical Resource Scheduling in Cloud Data Centers. In: Wang, G., Chen, B., Li, W., Di Pietro, R., Yan, X., Han, H. (eds) Security, Privacy, and Anonymity in Computation, Communication, and Storage. SpaCCS 2020. Lecture Notes in Computer Science(), vol 12383. Springer, Cham. https://doi.org/10.1007/978-3-030-68884-4_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-68884-4_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-68883-7

  • Online ISBN: 978-3-030-68884-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics