Skip to main content

Analysis of Cloud Environment Using CloudSim

  • Conference paper
  • First Online:
Artificial Intelligence and Evolutionary Computations in Engineering Systems

Abstract

Cloud computing is a thirst area of research since it provides very important services such as platform as a service (PaaS), infrastructure as a service (IaaS), mobile “backend” as a service (MBaaS), software as a service (SaaS) in the computing and communication environment. Improving the performance of these services is a major challenge being addressed by many researchers. In the recent past, the cloud environment is set up by the service providers and the service is provided to the user in on-demand basis. The quality of the services provided by cloud computing highly depends on the performance of the cloud computing setup or environment (cloud setup). Developing the real cloud environment and evaluating their performance is impractical as it requires huge investment. Hence, researchers use simulation tools to evaluate the performance of cloud computing before constructing the cloud. The CloudSim is a cloud simulation tool for modeling and simulating the cloud computing environment. This paper presents a performance analysis of cloud computing environment using CloudSim.

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 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
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. http://www.cloudbus.org/cloudsim/

  2. M. Satyanarayanan, P. Bahl, R. Cáceres, N. Davies, The case for VM-based cloudlets in mobile computing. IEEE Trans. Pervasive Comput. 8(4), 14–23 (2009)

    Google Scholar 

  3. R. Malhotra, P. Jain, Study and comparison of CloudSim simulators in the cloud computing. SIJ Trans. Comput. Sci. Eng. Appl. (CSEA) 1(4) (2013)

    Google Scholar 

  4. N. Khanghahi, R. Ravanmehr, Cloud computing performance evaluation: Issues and challenges. Int. J. Cloud Comput. Serv. Archit. (ijccsa) 3(5) (2013)

    Google Scholar 

  5. R. Buyya, R. Ranjan, R. N. Calheiros, Modeling and simulation of scalable cloud computing environments and the CloudSim toolkit: challenges and opportunities. IEEE, Issue No: 978-1-4244-4907 (2009)

    Google Scholar 

  6. A. Gupta, P. Faraboschi, F. Gioachin, L.V. Kale, R. Kaufmann, B.-S. Lee, V. March, D. Milojicic, C.H. Suen, Evaluating and improving the performance and scheduling of HPC applications in cloud. IEEE Trans. Cloud Comput. 10.1109, 2339858 (2014)

    Google Scholar 

  7. S. Khurana, K. Marwah, Performance evaluation of virtual machine (VM) scheduling policies in cloud computing (Spaceshared & Timeshared). IEEE—31661, 4th ICCCNT (2013)

    Google Scholar 

  8. R.N. Calheiros, R. Ranjan, R. Buyya, Virtual machine provisioning based on analytical performance and QoS in cloud computing environments, in International conference on Parallel Processing, pp. 295–305 (2011)

    Google Scholar 

  9. L.S. Nishad, S. Kumar, S.K. Bola, S. Beniwal, A. Pareek, Round Robin selection for data center simulation technique CloudSim and CloudAnalyst architecture and making it efficient by using load balancing algorithm. IEEE 978-9-3805-4421 (2016)

    Google Scholar 

  10. M.A. Rodriguez, R. Buyya, Deadline based resource provisioning and scheduling algorithm for scientific workflows on clouds. IEEE Trans. Cloud Comput. 2314655 (2014)

    Google Scholar 

  11. X. Zhu, C. Chen, L.T. Yang, Y. Xiang, ANGEL: agent-based scheduling for real-time tasks in virtualized cloud. IEEE Trans. Comput. 10.1109, 2409864 (2015)

    Google Scholar 

  12. I.S. Moreno, P. Garraghan, P. Townend, J. Xu, Analysis, modeling and simulation of workload patterns in a large-scale utility cloud. IEEE Trans. Cloud Comput. 2(2) (2014)

    Google Scholar 

  13. D. Bruneo, A. Lhoas, F. Longo, A. Puliafito, Modeling and evaluation of energy policies in green clouds. IEEE Trans. Parallel Distrib. Syst. 10.1109, 2364194 (2014)

    Google Scholar 

  14. N. Kumar, S. Saxena, Migration performance of cloud applications—a quantitative analysis, in International Conference on Advanced Computing Technologies and Applications. Proc. Comput. Sci. 45,823–831 (2015) (Elsevier)

    Google Scholar 

  15. W. Long, L. Yuqing, X. Qingxin, Using CloudSim to model and simulate cloud computing environment, in Ninth International Conference on Computational Intelligence and Security, IEEE, Issue No: 978-1-4799-2548-3 (2013)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to D. Asir Antony Gnana Singh .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Asir Antony Gnana Singh, D., Priyadharshini, R., Jebamalar Leavline, E. (2018). Analysis of Cloud Environment Using CloudSim. In: Dash, S., Naidu, P., Bayindir, R., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 668. Springer, Singapore. https://doi.org/10.1007/978-981-10-7868-2_32

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-7868-2_32

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7867-5

  • Online ISBN: 978-981-10-7868-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics