Skip to main content

AutoCSD: Automatic Cloud System Deployment in Data Centers

  • Conference paper
  • First Online:
Book cover Cloud Computing and Big Data (CloudCom-Asia 2015)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9106))

  • 1319 Accesses

Abstract

It is a huge challenge to deploy a cloud computing system in large-scale data centers. In order to help resolve this issue, we propose an automatic cloud system deployment approach with the characteristics of reliability, availability, and load balance. Specifically, we use workflow to deal with the dependencies among the automatic deployment processes of a cloud system. We also design a failover mechanism to avoid the single point failure of the deployment server. Besides, we adopt a load balancing algorithm to solve the bottleneck problem of deploying a cloud system.

We implement a prototype, and evaluate it with 16 physical nodes as well as a virtualized environment with 160 virtual machines. Experimental results show that the average deployment time under our approach is lower than that with traditional deployment methods. In addition, it achieves a cloud system deployment success ratio of up to 90 %, even in the high-concurrency environment.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Systemimager. http://sourceforge.net/projects/systemimager/?source=navbar. Accessed February 2015

  2. Kickstart. https://access.redhat.com/documentation/en-US/Red_Hat_Enterprise_Linux/5/html/Installation_Guide/ch-kickstart2.html. Accessed February 2015

  3. Devstack. http://docs.openstack.org/developer/devstack/overview.html. Accessed February 2015

  4. Mell, P., Grance, T.: The nist definition of cloud computing. Nat. Inst. Stand. Technol. 53(6), 50 (2009)

    Google Scholar 

  5. Amazon ec2. http://aws.amazon.com/ec2/. Accessed February 2015

  6. Sefraoui, O., Aissaoui, M., Eleuldj, M.: Openstack: toward an open-source solution for cloud computing. Int. J. Comput. Appl. 55(3), 38–42 (2012)

    Google Scholar 

  7. Nurmi, D., Wolski, R., Grzegorczyk, C., Obertelli, G., Soman, S., Youseff, L., Zagorodnov, D.: The eucalyptus open-source cloud-computing system. In Proccedings of 9th IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID 2009), pp. 124–131. IEEE (2009)

    Google Scholar 

  8. Cortes, T.: Software raid and parallel file systems. In: High Performance Cluster Computing, pp. 463–496 (1999)

    Google Scholar 

  9. Linux channel bonding. http://sourceforge.net/projects/bonding/. Accessed February 2015

  10. Heartbeat. http://linux-ha.org/wiki/Heartbeat. Accessed February 2015

  11. Crane cloud system. http://www.chinagrid.edu.cn. Accessed February 2015

  12. Rackspace cloud. http://www.rackspace.com/. Accessed February 2015

  13. Microsoft azure. http://azure.microsoft.com/. Accessed February 2015

  14. Google app engine. https://appengine.google.com/. Accessed February 2015

  15. Prodan, R., Sperk, M.: Scientific computing with google app engine. Future Gener. Comput. Syst. 29(7), 1851–1859 (2013)

    Article  Google Scholar 

  16. Chen, H.-S., Wu, C.-H., Pan, Y.-L., Yu, H.-E., Chen, C.-M., Cheng, K.-Y.: Towards the automated fast deployment and clone of private cloud service: the ezilla toolkit. In: Proceedings of 2013 IEEE 5th International Conference on Cloud Computing Technology and Science (CloudCom), vol. 1, pp. 136–141. IEEE (2013)

    Google Scholar 

  17. Sobeslav, V., Komarek, A.: Opensource automation in cloud computing. In: Wong, W.E. (ed.) Proceedings of the 4th International Conference on Computer Engineering and Networks, pp. 805–812. Springer (2015)

    Google Scholar 

Download references

Acknowledgement

The research is supported by National Science Foundation of China under grants No. 61232008, National 863 Hi-Tech Research & Development Program under grants No. 2014AA01A302 and No. 2015AA011402, Research Fund for the Doctoral Program of MOE under grant No. 20110142130005, Anhui Provincial Natural Science Foundation under grant No.1408085MF126, Youth Foundation of Chuzhou University under grant No. 2013RC006 and Scientific Research Foundation of Chuzhou University under grant No. 2014qd016.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Haibao Chen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Xie, T., Chen, H. (2015). AutoCSD: Automatic Cloud System Deployment in Data Centers. In: Qiang, W., Zheng, X., Hsu, CH. (eds) Cloud Computing and Big Data. CloudCom-Asia 2015. Lecture Notes in Computer Science(), vol 9106. Springer, Cham. https://doi.org/10.1007/978-3-319-28430-9_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-28430-9_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28429-3

  • Online ISBN: 978-3-319-28430-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics