Advertisement

Designing of an Orchestration Mechanism for the Efficient Web-Services Composition

  • Reena Gupta
  • Raj Kamal
  • Ugrasen Suman
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 710)

Abstract

Service-oriented architecture (SOA) is an emerging paradigm to build complex applications and business processes. SOA is described by the interactions between the loosely coupled, coarse-grained, and autonomous services. The interactions take place in a distributed environment. The services need interoperability for the heterogeneous applications and complex business processes. Web-services composition (WSC) is thus an important aspect of applications and processes. Two major approaches for the WSCs are orchestration and choreography. The orchestration offers number of advantages over choreography during the WSC. The paper gives a literature review of different approaches and of the tools, which are available for Web-services orchestration (WSO). The paper describes a comparison of earlier WSO approaches taking into account different benchmarks and identifies the needs of the improvements. The paper suggests an orchestration-based improved approach during the WSC and needed steps for that.

Keywords

Service-oriented architecture Web-services Web-services composition Orchestration Choreography Dynamic 

References

  1. 1.
    Josuttis, N.M.: SOA in Practice: The Art of Distributed System Design. O’Reilly Media, Sebastopol, CA, USA (2007).Google Scholar
  2. 2.
    Rathore, M., Suman, U.: A Quality of Service Broker Based Process Model for Dynamic Web Service Composition. J. Comput. Sci. 7(8), 1267-1274 (2011).Google Scholar
  3. 3.
    Juric, M.B.: A Hands-on Introduction to BPEL http://www.oracle.com/technetwork/articles/matjaz-bpel1-090575.html.
  4. 4.
    Karande, A., Karande, M., Meshram, B.B.: Choreography and Orchestration using Business Process Execution Language for SOA with Web Services. Int. J. Comput. Sci. Issues 8(2), 224–232 (2011).Google Scholar
  5. 5.
    Albreshne, A., Fuhrer, P., Pasquier, J.: Web Services Orchestration and Composition. Working Paper (2009).Google Scholar
  6. 6.
    Liu, Z., Wang, H., Xu, X., Wang, Z.: Web services optimal composition based on improved artificial bee colony algorithm with the knowledge of service domain features. Int. J. Serv. Comput. 4(1), 27–38 (2016).Google Scholar
  7. 7.
    Chitra, A., Guptha, M.N.: QoS Aware Adaptive Service Composition. Res. J. Appl. Sci. Eng. Technol. 7(19), 4072–4078 (2014).Google Scholar
  8. 8.
    Mohamed, M., Amine, C.M., Amina, B.: Immune-inspired method for selecting the optimal solution in semantic web service composition. Int. J. Web Semant. Technol. 5(4), 21–31 (2014).Google Scholar
  9. 9.
    Yu, D., Li, C., Yin, Yu.: Optimizing web service composition for Data-intensive applications. Int. J. Database Theor. Appl. 7(2), 1–12 (2014).Google Scholar
  10. 10.
    Mohamed, M.F., EIYamany, H.F., Nassar, H.M.: A study of an adaptive replication framework for orchestrated composite web services. SpringerPlus 2, 511 (2013).Google Scholar
  11. 11.
    Arul, U., Prakash, D.S.: Towards Fault Handling In B2b Collaboration Using Orchestration Based Web Services Composition. Int. J. Emerg. Technol. Adv. Eng. 3(1), 388–394 (2013).Google Scholar
  12. 12.
    Zhao, X., Huang, P., Liu, T., Li, X.: A Hybrid Clonal Selection Algorithm for Quality of Service-Aware Web Service Selection Problem. Int. J. Innov. Comput. Inf. Control 8(12), 8527–8544 (2012).Google Scholar
  13. 13.
    Liu, M., Wang, M., Shen, W., Luo, N., Yan, J.: A quality of service (QoS)-aware execution plan selection approach for a service composition process. Future Gener. Comput. Syst. 28, 1080–1089 (2012).Google Scholar
  14. 14.
    Baird, R., Jorgenson, N., Gamble, R.: Self-adapting workflow reconfiguration. J. Syst. Softw. 84(3), 510–524 (2011).Google Scholar
  15. 15.
    Lin, C.F., Sheu, R.K., Chang, Y.S., Yuan, S.M.: A relaxable service selection algorithm for QoS-based web service composition. Inf. Softw. Technol. 53(12), 1370–1381(2011).Google Scholar
  16. 16.
    Wu, M., Xiong, X., Ying, J., Jin, C., Yu, C.: QoS-driven global optimization approach for large-scale web services composition. J. Comput. 6(7), 1452–1460 (2011).Google Scholar
  17. 17.
    Wu, Y., Wang, X.: Applying multi-objective genetic algorithms to QoS-aware web service global selection. Adv. Inf. Sci. Serv. Sci. 3(11), 473–482 (2011).Google Scholar
  18. 18.
    Bin, X., Sen, L., Yixin, Y.: Efficient Composition of Semantic Web Services with End-to-End QoS optimization. Tsinghua Sci. Technol. 15(6), 678–686 (2010).Google Scholar
  19. 19.
    Wang, W., Sun, Q., Zhao, X., Yang, F.: An improved particle swarm optimization algorithm for QoS-aware web service selection in service oriented communication. Int. J. Comput. Intell. Syst. 3(1), 18–30 (2010).Google Scholar
  20. 20.
    Haung, A.F.M., Lan, C.W., Yang, S.J.H.: An optimal QoS-based web service selection scheme. Inf. Sci. 179, 3309–3322 (2009).Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.School of Computer Science & Information TechnologyDevi Ahilya UniversityIndoreIndia

Personalised recommendations