Skip to main content
SpringerLink
Log in

Framework for web service composition based on QoS in the multi cloud environment

  • Original Research
  • Published:
International Journal of Information Technology Aims and scope Submit manuscript

Abstract

Recently, the term cloud computing is widely used in the searching community, which shows the importance given by the scientists to this research area; cloud computing is a new computing model provides shared resources and data based on service delivery model, where everything from infrastructures, platforms, and software are given to the user like a set of services. The users of cloud platforms deal with these services to satisfy their requests, however these requests become more complex, and they need more than one service to accomplish one request; the process of gathering a set of services to satisfy a user request is called the service composition. In addition to the fact that one request needs a set of services to be executed, and die to the quick development of cloud technology, there are many of similar services which offer the same functionality, for each service in this set, which make the composition process needs a mechanism to choose between these infinity choices to give the user an optimal satisfaction. In this paper, We propose a framework for service composition in the multi cloud environment where we compose these services based on two factors: the first is a set of QoS (quality of service) criteria for each service, and the second is the number of cloud bases involved in the composition process, to build a composed service that satisfy the user request.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Al-Masri E, Mahmoud QH (2007) Discovering the best web service. In: Proceedings of the 16th international conference on World Wide Web. ACM, New York, pp 1257–1258. https://doi.org/10.1145/1242572.1242795

  2. Al-Masri E, Mahmoud QH (2007) QoS-based discovery and ranking of web services. In: Proceedings of 16th international conference on computer communications and networks, 2007. ICCCN 2007. IEEE, New York, pp 529–534. https://doi.org/10.1109/ICCCN.2007.4317873

  3. Barkat A, Okba K, Bourekkach S (2017) Service composition in the multi cloud environment. Int J Web Inf Syst 13(4):471–484. https://doi.org/10.1108/IJWIS-08-2016-0047

    Article  Google Scholar 

  4. Bennajeh A, Hachicha H (2015) Web Service Composition Based on a Multi-agent System. Software Engineering in Intellignt Systems. Springer, pp 295–305

  5. Huo Y, Zhuang Y, Gu J, Ni S, Xue Y (2015) Discrete gbest-guided artificial bee colony algorithm for cloud service composition. Appl Intell 42(4):661–678. https://doi.org/10.1007/s10489-014-0617-y

    Article  Google Scholar 

  6. Jula A, Sundararajan E, Othman Z (2014) Cloud computing service composition: a systematic literature review. Expert Syst Appl 41:3809–3824. https://doi.org/10.1016/j.eswa.2013.12.017

    Article  Google Scholar 

  7. Kurdi H, Al-Anazi A, Campbell C, Al Faries A (2015) A combinatorial optimization algorithm for multiple cloud service composition. Comput Electr Eng 42:107–113. https://doi.org/10.1016/j.compeleceng.2014.11.002

    Article  Google Scholar 

  8. Mell P, Grance T (2011) The NIST definition of cloud computing. Computer Security Division Information Technology Laboratory National Institute of Standards and Technology Gaithersburg, MD 20899-8930 September 2011

  9. Rath M (2019) Resource provision and QoS support with added security for client side applications in cloud computing. Int J Inf Technol 11(2):357–364. https://doi.org/10.1007/s41870-017-0059-y

    Article  Google Scholar 

  10. Shah-Hosseini H (2008) Intelligent water drops algorithm: a new optimization method for solving the multiple knapsack problem. Int J Intell Comput Cybern 1(2):193–212. https://doi.org/10.1108/17563780810874717

    Article  MathSciNet  MATH  Google Scholar 

  11. Shah-Hosseini H (2009) The intelligent water drops algorithm: a nature-inspired swarm-based optimization algorithm. Int J BioInspired Comput 1(1–2):71–79. https://pdfs.semanticscholar.org/9d61/b5d40f561a08657e75350c58a0e842be00c7.pdf

  12. Tao F, Zhao D, Hu Y, Zhou Z (2008) Resource service composition and its optimal-selection based on particle swarm optimization in manufacturing grid system. IEEE Trans Ind Inform 4(4):315–327. https://doi.org/10.1109/TII.2008.2009533

    Article  Google Scholar 

  13. Yang Z, Shang C, Liu Q, Zhao C (2010) A dynamic web services composition algorithm based on the combination of ant colony algorithm and genetic algorithm. J. Comput. Inf. Syst. 8:2617–2622

    Google Scholar 

  14. Yu Q, Chen L, Li B (2015) Ant colony optimization applied to web service compositions in cloud computing. Comput Electr Eng 41:18–27. https://doi.org/10.1016/j.compeleceng.2014.12.004

    Article  Google Scholar 

  15. Yu Y, Ma H, Zhang M (2014) A genetic programming approach to distributed QoS-aware web service composition. In: 2014 IEEE Congress on evolutionary computation (CEC). IEEE, New York, pp 1840–1846. https://doi.org/10.1109/CEC.2014.6900416

  16. Zaki Brahmi MF (2014) Service Composition in a Multi-Cloud environment based on Cooperative Agents. In: SRMC 2014: International Workshop on Scheduling and Resource Management in Cloud, 2014

  17. Zeng L, Benatallah B, Ngu AHH, Dumas M, Kalagnanam J, Chang H (2004) QoS-aware middleware for web services composition. IEEE Trans Softw Eng 30(5):311–327. https://doi.org/10.1109/TSE.2004.11

    Article  Google Scholar 

  18. Zeng L, Benatallah B, Ngu AHH, Dumas M, Kalagnanam J, Chang H (2004) QoS-aware middleware for Web services composition. IEEE Trans Softw Eng 30(5):311–327

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, M’sila University, M’sila, Algeria

    Abdelbasset Barkat

  2. LINFI Laboratory, Department of Computer Science, University of Mohamed Khider Biskra, Biskra, Algeria

    Okba Kazar

  3. Department of Computer Science, Bordj Bou Arreridj University, Bordj Bou Arreridj, Algeria

    Imane Seddiki

Authors
  1. Abdelbasset Barkat
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Okba Kazar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Imane Seddiki
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Abdelbasset Barkat.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Barkat, A., Kazar, O. & Seddiki, I. Framework for web service composition based on QoS in the multi cloud environment. Int. j. inf. tecnol. 13, 459–467 (2021). https://doi.org/10.1007/s41870-020-00564-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41870-020-00564-z

Keywords

Search

Navigation