Skip to main content
SpringerLink
Log in

Budget-Aware Performance Optimization of Workflows in Multiple Data Center Clouds

  • Conference paper
  • First Online:
Mobile, Secure, and Programmable Networking (MSPN 2020)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 12605))

  • 343 Accesses

Abstract

Users pay to use resources in cloud systems which makes them more demanding on performance and costs. Optimizing the response time of the applications and meeting user’s budget needs are therefore critical requirements when scheduling applications.

The approach presented in this work is a scheduling based-HEFT algorithm, which aims to optimize the makespan of tasks workflow that is constrained by the budget. For this, we propose a new budget distribution strategy named Estimated task budget that we integrate in our budget-aware HEFT algorithm. We use a multiple datacenters cloud as a real platform model, where data transfer costs are considered. The results obtained by our algorithm relative to recent work, show an improvement of makespan in the case of a restricted budget, without exceeding the given budget.

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

Access this chapter

Log in via an institution
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

Notes

  1. 1.

    https://confluence.pegasus.isi.edu/display/pegasus/WorkflowGenerator.

References

  1. Arabnejad, V., Bubendorfer, K., Ng, B.: Budget distribution strategies for scientific workflow scheduling in commercial clouds. In: 2016 IEEE 12th International Conference on e-Science (e-Science), pp. 137–146. IEEE (2016)

    Google Scholar 

  2. Arabnejad, V., Bubendorfer, K., Ng, B.: Budget and deadline aware e-science workflow scheduling in clouds. IEEE Trans. Parallel Distrib. Syst. 30(1), 29–44 (2018)

    Article  Google Scholar 

  3. Braun, T.D., et al.: A comparison of eleven static heuristics for mapping a class of independent tasks onto heterogeneous distributed computing systems. J. Parallel Distrib. Comput. 61(6), 810–837 (2001)

    Article  Google Scholar 

  4. Brucker, P.: Scheduling Algorithms, vol. 3. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-69516-5

    Book  MATH  Google Scholar 

  5. Caniou, Y., Caron, E., Chang, A.K.W., Robert, Y.: Budget-aware scheduling algorithms for scientific workflows with stochastic task weights on heterogeneous IAAS cloud platforms. In: 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 15–26. IEEE (2018)

    Google Scholar 

  6. Kalyan Chakravarthi, K., Shyamala, L., Vaidehi, V.: Budget aware scheduling algorithm for workflow applications in IAAS clouds. Cluster Comput. 1–15 (2020)

    Google Scholar 

  7. Fahringer, T., Jugravu, A., Pllana, S., Prodan, R., Seragiotto Jr., C., Truong, H.-L.: Askalon: a tool set for cluster and grid computing. Concurrency and Computation: Practice and Experience 17(2–4), 143–169 (2005)

    Article  Google Scholar 

  8. Ghafouri, R., Movaghar, A., Mohsenzadeh, M.: Time-cost efficient scheduling algorithms for executing workflow in infrastructure as a service clouds. Wireless Pers. Commun. 103(3), 2035–2070 (2018)

    Article  Google Scholar 

  9. Han, P., Du, C., Chen, J., Ling, F., Du, X.: Cost and makespan scheduling of workflows in clouds using list multiobjective optimization technique. J. Syst. Archit. 101837 (2020)

    Google Scholar 

  10. Pingping, L., Zhang, G., Zhu, Z., Zhou, X., Sun, J., Zhou, J.: A review of cost and makespan-aware workflow scheduling in clouds. J. Circuits, Syst. Comput. 28(06), 1930006 (2019)

    Article  Google Scholar 

  11. Oukfif, K., Bouali, L., Bouzefrane, S., Oulebsir-Boumghar, F.: Energy-aware DPSO algorithm for workflow scheduling on computational grids. In: 2015 3rd International Conference on Future Internet of Things and Cloud (FiCloud), pp. 651–656. IEEE (2015)

    Google Scholar 

  12. Oukfif, K., Oulebsir-Boumghar, F., Bouzefrane, S., Banerjee, S.: Workflow scheduling with data transfer optimisation and enhancement of reliability in cloud data centres. Int. J. Commun. Networks Distrib. Syst. 24(3), 262–283 (2020)

    Article  Google Scholar 

  13. Rodriguez, M.A., Buyya, R.: Budget-driven scheduling of scientific workflows in IAAS clouds with fine-grained billing periods. ACM Trans. Auton. Adapt. Syst. (TAAS) 12(2), 1–22 (2017)

    Article  Google Scholar 

  14. Topcuoglu, H., Hariri, S., Min-you, W.: Performance-effective and low-complexity task scheduling for heterogeneous computing. IEEE Trans. Parallel Distrib. Syst. 13(3), 260–274 (2002)

    Article  Google Scholar 

  15. Verma, A., Kaushal, S.: Cost-time efficient scheduling plan for executing workflows in the cloud. J. Comput. 13(4), 495–506 (2015)

    MathSciNet  Google Scholar 

  16. Fuhui, W., Qingbo, W., Tan, Y.: Workflow scheduling in cloud: a survey. J. Supercomput. 71(9), 3373–3418 (2015)

    Article  Google Scholar 

  17. Zheng, W., Sakellariou, R.: Budget-deadline constrained workflow planning for admission control. J. Grid Comput. 11(4), 633–651 (2013)

    Article  Google Scholar 

  18. Zhou, N., Lin, W., Feng, W., Shi, F., Pang, X.: Budget-deadline constrained approach for scientific workflows scheduling in a cloud environment. Cluster Comput. 1–15 (2020)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. LARI Lab, Mouloud Mammeri University of Tizi-Ouzou, Tizi-Ouzou, Algeria

    Karima Oukfif

  2. University of Lille, Lille, France

    Fares Battou

  3. CEDRIC Lab, Conservatoire National des Arts et Metiers, Paris, France

    Samia Bouzefrane

Authors
  1. Karima Oukfif
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fares Battou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Samia Bouzefrane
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Karima Oukfif .

Editor information

Editors and Affiliations

  1. Cedric Lab, Cnam, Paris, France

    Samia Bouzefrane

  2. Télécom SudParis, Evry, France

    Maryline Laurent

  3. Cedric Lab, Cnam, Paris, France

    Selma Boumerdassi

  4. LIGM, ESIEE, Noisy-le-Grand, France

    Eric Renault

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

Oukfif, K., Battou, F., Bouzefrane, S. (2021). Budget-Aware Performance Optimization of Workflows in Multiple Data Center Clouds. In: Bouzefrane, S., Laurent, M., Boumerdassi, S., Renault, E. (eds) Mobile, Secure, and Programmable Networking. MSPN 2020. Lecture Notes in Computer Science(), vol 12605. Springer, Cham. https://doi.org/10.1007/978-3-030-67550-9_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-67550-9_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-67549-3

  • Online ISBN: 978-3-030-67550-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation