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A QoS-aware Service Selection Method for Configuring Web Service Composition

웹 서비스 합성 구성을 위한 QoS고려 서비스 선택 기법

  • 윤경아 (숙명여자대학교 컴퓨터과학과) ;
  • 김윤희 (숙명여자대학교 컴퓨터과학부)
  • Received : 2012.01.25
  • Accepted : 2012.05.30
  • Published : 2012.08.31

Abstract

To fulfill the complex user requirement, composition web service comprised of existing services is considered from the efficient and reusable point of view instead of making entirely new web service. However, with the growing the number of web services which provide the same functionality but differ in quality value, the service composition becomes a decision problem on which component services should be selected such that end-to-end QoS constraints by the client and overall QoS of the composition service are satisfied. QoS of service aspects is a determinant factor for selecting the services, since the performance of the composed service is determined by the performance of the involved component web service. In this paper, hybrid genetic algorithm is presented to select component services to take part in the QoS-aware composition. The local search method is used to be combined with the genetic algorithm to improve the individuals (component service) in population as well as composed service. The paper also presents a set of experiments conducted to evaluate the efficiency of selection algorithm using the real web service data.

웹 서비스 합성은 기존 단일 서비스들을 합성해서 제공하는 방식으로, 사용자의 다양한 요구를 만족시키기 위해서 새로운 웹 서비스를 만들기보다는 재사용과 효율성 측면에서 고려되고 있다. 그러나 유사 기능을 제공하지만 다른 서비스 품질을 제공하는 서비스의 수가 증가함에 따라, 서비스 합성 문제는 사용자의 전역 제약 조건과 합성서비스의 QoS를 만족시키기 위해서 어떤 구성 서비스들을 선택해야 하는지에 대한 선택 문제가 되었다. 합성 서비스의 수행은 구성 서비스의 수행에 의해 결정되므로, 합성 서비스에 포함될 구성 서비스 선택을 위해서는 가격, 지속성, 응답시간과 같은 QoS에 대한 고려는 필수적이다. 본 논문에서는 합성 서비스 선택 시 QoS를 고려한 기법으로 합성 유전자 알고리즘을 적용하였다. 유전자 알고리즘에 지역 탐색 방법을 결합하여 빠른 시간 안에 합성 서비스의 전반적인 QoS뿐만 아니라 구성 서비스의 품질을 향상 시킬 수 있는 서비스 선택 기법을 제시한다. 본 연구는 실제 웹상에 존재하는 실제 데이터를 이용하여 서비스 증가에 따른 시간 측정 및 최적화 정도를 비교 분석을 통해 선택 알고리즘의 유효성을 검증하였다.

Keywords

References

  1. Mohammad A and Thomas R, "Combining global optimization with local selection for efficient QoS-aware service composition", Proceedings of the 18th international conference on World wide web, April 20-24, 2009
  2. Ardagna D and Pernici B, "Global and local QoS guarantee in web service selection", In: Proc. of Business Process Management Workshops, pp.32-46, 2006.
  3. Cardellin V, Casalicchio E, Grassi V, Francesco LP, "Flow-based service selection for web service composition supporting multiple QoS classes", In: ICWS 2007. IEEE Intl. Conf. Web Services, pp.743-750, 2007.
  4. Zeng L, Benatallah B, Ngu AHH, Dumas, M, Kalagnanam, J. Chang, H.: "Qos-aware middleware for web services composition", IEEE Trans. Software Eng. 30, 311-327, 2004. https://doi.org/10.1109/TSE.2004.11
  5. Z.-J. Wang, Z.-Z. Liu, X.-F. Zhou and Y.-S. Lou, "An approach for composite web service selection based on DGQoS", Int J Adv Manuf Technol, The International Journal of Advanced Manufacturing Technology, 56:1167-1179, 2011. https://doi.org/10.1007/s00170-011-3230-9
  6. Gerardo C, Penta MD, Esposito R, Villani ML "An approach for QoS-aware service composition based on genetic algorithms". In: Proceedings of the 2005 Conference on Genetic and Evolutionary Computation, pp.1069-1075, 2005.
  7. memetic algorithm, http://ko.wikipedia.org/
  8. H. C.-L and K. Yoon Multiple Criteria Decision Making. Lecture Notes in Economics and Mathematical Systems, Springer-Verlag, 1981.
  9. SeongGon Kong, InTeac Kim, DaeHee Park, ect, "An Introduction to Genetic Algorithms", Seoul: Green, 1996.
  10. Y. Ma and C. Zhang, "Quick Convergence of Genetic Algorithm for QoS-Driven Web Service Selection", Computer Networks, Vol.52, No.5, pp.1093-1104, 2008. https://doi.org/10.1016/j.comnet.2007.12.003
  11. Matlab, Web page. http://www.mathworks.com/
  12. Evolutionary Computation Research Team, Genetic Algorithm Toolbox, Web page. http://www.shef.ac.uk/acse/research/ecrg/gat
  13. E. Al-Masri and Q. H. Mahmoud. "Investigating web services on the world wide web", In Proceedings of the International World Wide Web Conference, 2008.
  14. E. Al-Masri and Q. H. Mahmoud. "Qos-based discovery and ranking of web services", In Proceedings of the IEEE International Conference on Computer Communications and Networks, 2007.
  15. E. Al-Masri and Q. H. Mahmoud. The qws dataset. Web page. http://www.uoguelph.ca/-qmahmoud/qws/index.html/.
  16. J. Cardoso, J. Miller, A. Sheth, and J. Arnold. "Quality of service for workflows and web service processes", Journal of Web Semantics, 1:281-308, 2004. https://doi.org/10.1016/j.websem.2004.03.001
  17. Tang ML, Ai LF, "A hybrid genetic algorithm for the optimal constrained web service selection problem in web service composition", WCCI 2010 IEEE World Congress on Computational Intelligence, IEEE, pp.268-275, 30 Jul., 2010.