Skip to main content

Allocation of Cloud Resources in a Dynamic Way Using an SLA-Driven Approach

  • Conference paper
  • First Online:
Proceedings of the 2nd International Conference on Data Engineering and Communication Technology

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 828))

  • 1079 Accesses

Abstract

Cloud computing provides a wide access to complex applications running on virtualized hardware with its support for elastic resources that are available in an on-demand manner. In cloud environment, multiple users can request resources simultaneously and so it has to be made available to them in an efficient manner. For the efficient utilization, these computing resources can be dynamically configured according to varying workload. Here in this paper, we proposed an efficient resource management system to allocate elastic resources dynamically according to dynamic workload.

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. Ali S, Jing S-Y, Kun S (2013) Profit-aware dvfs enabled resource management of iaas cloud. Int J Comput Sci Issues (IJCSI) 10:237

    Google Scholar 

  2. Padala P, Shin KG, Zhu X, Uysal M, Wang Z, Singhal S, Merchant A, Salem K (2007) Adaptive control of virtualized resources in utility computing environments. In: ACM SIGOPS operating systems review, vol 41, no 3. ACM, 2007, pp 289–302

    Google Scholar 

  3. Ruth P, McGachey P, Xu D (2005) Viocluster: virtualization for dynamic computational domains. In: IEEE international cluster computing, IEEE pp 1–10

    Google Scholar 

  4. Emeneker W, Stanzione D (2007) Dynamic virtual clustering. In: IEEE international conference on cluster computing (2007). IEEE pp 84–90

    Google Scholar 

  5. Blanco CV, Huedo E, Montero RS, Llorente IM (2009) Dynamic provision of computing resources from grid infrastructures and cloud providers. In: Grid and pervasive computing conference, (2009) GPC’09. Workshops at the. IEEE pp 113–120

    Google Scholar 

  6. Murphy MA, Kagey B, Fenn M, Goasguen S (2009) Dynamic provisioning of virtual organization clusters. In: Proceedings of the 2009 9th IEEE/ACM international symposium on cluster computing and the grid. IEEE computer society, pp 364–371

    Google Scholar 

  7. De Assunção MD, Di Costanzo A, Buyya R (2009) Evaluating the cost-benefit of using cloud computing to extend the capacity of clusters. In: Proceedings of the 18th ACM international symposium on high performance distributed computing. ACM, pp 141–150

    Google Scholar 

  8. Silva JN, Veiga L, Ferreira P (2008) Heuristic for resources allocation on utility computing infrastructures. In: Proceedings of the 6th international workshop on middleware for grid computing. ACM, p 9

    Google Scholar 

  9. Zhang L, Ardagna D (2004) Sla based profit optimization in web systems. In: Proceedings of the 13th international world wide web conference on alternate track papers & posters. ACM, pp 462–463

    Google Scholar 

  10. Salehi MA, Buyya R (2010) Adapting market-oriented scheduling policies for cloud computing. In: International conference on algorithms and architectures for parallel processing. Springer, pp 351–362

    Google Scholar 

  11. Perros HG, Elsayed KM (1996) Call admission control schemes: a review. IEEE Commun Mag 34(11):82–91

    Article  Google Scholar 

  12. Kleinrock L (1975) Queuing systems. Wiley

    Google Scholar 

  13. Menasce DA, Almeida VA, Dowdy LW, Dowdy L (2004) Performance by design: computer capacity planning by example. Prentice Hall Professional

    Google Scholar 

  14. Papoulis A, Pillai SU (2002) Probability, random variables, and stochastic processes. Tata McGraw-Hill Education

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to S. Anithakumari .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Anithakumari, S., Chandrasekaran, K. (2019). Allocation of Cloud Resources in a Dynamic Way Using an SLA-Driven Approach. In: Kulkarni, A., Satapathy, S., Kang, T., Kashan, A. (eds) Proceedings of the 2nd International Conference on Data Engineering and Communication Technology. Advances in Intelligent Systems and Computing, vol 828. Springer, Singapore. https://doi.org/10.1007/978-981-13-1610-4_42

Download citation

  • DOI: https://doi.org/10.1007/978-981-13-1610-4_42

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1609-8

  • Online ISBN: 978-981-13-1610-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics