Skip to main content

Adaptive Cloudlet Scheduling Algorithm Using Three Phase Optimization Technique

  • Conference paper
  • First Online:
Advances of Science and Technology (ICAST 2018)

Abstract

The purpose of cloud computing is to give suitable access to the remote scattered resources. This is achieved through virtualization, which separates the physical computing resources into multiple virtual resources. The other technologies like grid, utility and distributed computing are the backbone of cloud computing. The scheduler plays important role because the user has to pay for the resource based on the time consumed during their usage. Currently, cloudlets and the virtual machines are scheduled according to FCFS and round robin which has higher latency. In order to reduce the latency and to have uniform distribution in scheduling the cloudlets to the Virtual Machines, this paper introduces called ACS3O algorithm which consists of 3 phases of optimization techniques using gang and dedicated processor scheduling to schedule the cloudlets. The proposed cloudlet scheduling algorithm optimizes few basic parameters like waiting time and makespan which have significant impact in the performance. Simulation is done in a Cloudsim environment to evaluate the proposed algorithm.

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. Roy, S., Banerjee, S., Chowdhury, K.R., Biswas, U.: Development and analysis of a three-phase cloudlet allocation algorithm. J. King Saud Univ. Comput. Inf. Sci. 29(4), 473–483 (2017)

    Google Scholar 

  2. Lavanya, M., Sahana, V., Swathi Rekha, K., Vaithiyanathan, V.: Adaptive load balancing algorithm using modified resource allocation strategies on infrastructure as a service cloud systems. ARPN J. Eng. Appl. Sci. 10(10), 4522–4526 (2015)

    Google Scholar 

  3. Agarwal, A., Jain, S.: Efficient optimal algorithm of task scheduling in cloud computing environment. Int. J. Comput. Trends Technol. (IJCTT) 9(7), 344–349 (2014)

    Article  Google Scholar 

  4. Bhavani, B.H., Guruprasad, H.S.: Resource provisioning techniques in cloud computing environment: a survey. Int. J. Res. Comput. Commun. Technol. 3(3), 395–401 (2014)

    Google Scholar 

  5. Chawla, Y., Bhonsle, M.: A study on scheduling methods in cloud computing. Int. J. Emerg. Trends Technol. Comput. Sci. 1(3), 12–17 (2012)

    Google Scholar 

  6. Mathew, T., Sekaran, K.C., Jose, J.: Study and analysis of various task scheduling algorithms in the cloud computing environment. In: International Conference on Advances in Computing, Communications and Informatics (ICACCI) (2014)

    Google Scholar 

  7. Tohidirad, Y., Abdezadeh, S., Soltani Aliabadi, Z., Azizi, A., Moradi, M.: Virtual machine scheduling in cloud computing environment. Int. J. Manag. Public Sect. Inf. Commun. Technol. 6(4), 1–6 (2015)

    Google Scholar 

  8. Liu, G., Li, J., Xu, J.: An improved min-min algorithm in cloud computing. In: Du, Z. (ed.) Proceedings of the 2012 International Conference of Modern Computer Science and Applications. AISC, vol. 191, pp. 47–52. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-33030-8_8

    Chapter  Google Scholar 

  9. Mao, Y., Chen, X., Li, X.: Max–min task scheduling algorithm for load balance in cloud computing. In: Patnaik, S., Li, X. (eds.) Proceedings of International Conference on Computer Science and Information Technology. AISC, vol. 255, pp. 457–465. Springer, New Delhi (2014). https://doi.org/10.1007/978-81-322-1759-6_53

    Chapter  Google Scholar 

  10. Domanai, S.G., Reddy, G.R.M.: Load balancing in cloud computing using modified throttled algorithm. In: IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) (2013)

    Google Scholar 

  11. Teyeb, H.: Integrated optimization in cloud environment, Networking and Internet architecture. Université Paris-saclay (2017)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sivasankaran Saravanan .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Lavanya, M., Santhi, B., Saravanan, S. (2019). Adaptive Cloudlet Scheduling Algorithm Using Three Phase Optimization Technique. In: Zimale, F., Enku Nigussie, T., Fanta, S. (eds) Advances of Science and Technology. ICAST 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 274. Springer, Cham. https://doi.org/10.1007/978-3-030-15357-1_24

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-15357-1_24

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-15356-4

  • Online ISBN: 978-3-030-15357-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics