KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
권호 표지
DOI QR코드

DOI QR Code

QoS and SLA Aware Web Service Composition in Cloud Environment

  • Wang, Dandan (School of Computer and Communication Engineering, University of Science and Technology Beijing) ;
  • Ding, Hao (School of Computer and Communication Engineering, University of Science and Technology Beijing) ;
  • Yang, Yang (School of Computer and Communication Engineering, University of Science and Technology Beijing) ;
  • Mi, Zhenqiang (School of Computer and Communication Engineering, University of Science and Technology Beijing) ;
  • Liu, Li (School of Automation, University of Science and Technology Beijing) ;
  • Xiong, Zenggang (School of Computer and Information Science, Hubei Engineering University)
  • Received : 2016.03.01
  • Accepted : 2016.10.24
  • Published : 2016.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

As a service-oriented paradigm, web service composition has obtained great attention from both academia and industry, especially in the area of cloud service. Nowadays more and more web services providing the same function but different in QoS are available in cloud, so an important mission of service composition strategy is to select the optimal composition solution according to QoS. Furthermore, the selected composition solution should satisfy the service level agreement (SLA) which defines users' request for the performance of composite service, such as price and response time. A composite service is feasible only if its QoS satisfies user's request. In order to obtain composite service with the optimal QoS and avoid SLA violations simultaneously, in this paper we first propose a QoS evaluation method which takes the SLA satisfaction into account. Then we design a service selection algorithm based on our QoS evaluation method. At last, we put forward a parallel running strategy for the proposed selection algorithm. The simulation results show that our approach outperforms existing approaches in terms of solutions' optimality and feasibility. Through our running strategy, the computation time can be reduced to a large extent.

Keywords

References

  1. M. Bichler and K.J. Lin, "Service-oriented computing," IEEE Computer, vol. 39, no. 3, pp. 99-101, 2006.
  2. D. Guinard, V. Trifa, S. Karnouskos, P. Spiess, and D. Savio, "Interacting with the SOA-based internet of things: discovery, query, selection, and on-demand provisioning of Web services," Services Computing IEEE Transactions on, vol. 3, no. 3, pp. 223-235, 2010. https://doi.org/10.1109/TSC.2010.3
  3. S. Stein, T.R. Payne, and N.R. Jennings, "Robust execution of service workflows using redundancy and advance reservations," Services Computing IEEE Transactions on, vol. 4, no. 2, pp. 125-139, 2011. https://doi.org/10.1109/TSC.2010.47
  4. L. Zeng, H. Lei, and H. Chang, "Monitoring the QoS for Web services," in Proc. of International Conference on Service-Oriented Computing, Springer-Verlag, pp. 132-144, 2007.
  5. Z. Zheng, Y. Zhang, and M.R. Lyu, "Investigating QoS of real-world Web services," Services Computing IEEE Transactions on, vol. 7, no. 1, pp.32-39, 2014. https://doi.org/10.1109/TSC.2012.34
  6. M. Silic, G. Delac, I. Krka, and S. Srbljic, "Scalable and accurate prediction of availability of atomic Web services," Services Computing IEEE Transactions on, vol. 7, no. 2, pp. 252-264, 2014. https://doi.org/10.1109/TSC.2013.3
  7. P. Zhang, Z. Yan, "A QoS-aware system for mobile cloud computing," in Proc. of IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS), pp. 518-522, 2011.
  8. M. Alrifai, T. Risse, P. Dolog, and W. Nejdl, "A scalable approach for qos-based Web service selection," in Proc. of Service-Oriented Computing-ICSOC 2008 Workshops, Springer Berlin Heidelberg, pp. 190-199, 2009.
  9. M. Alrifai and T. Risse, "Combining global optimization with local selection for efficient qos-aware service composition," in Proc. of the 18th International Conference on World Wide Web, pp. 881-890, 2009.
  10. M. Alrifai, D. Skoutas, and T. Risse, "Selecting skyline services for qos-based Web service composition," in Proc. of the 19th International Conference on World Wide Web, ACM Press, pp. 11-20, 2010.
  11. T. Yu, Y. Zhang, K. J. Lin, "Efficient algorithms for Web services selection with end-to-end qos constraints," ACM Transactions on Web, vol. 1, no. 1, pp.1 -25, 2007. https://doi.org/10.1145/1232722.1232723
  12. G. Zou, Q. Lu, Y. Chen, R. Huang, Y. Xu, and Y. Xiang, "QoS-aware dynamic composition of Web services using numerical temporal planning," Services Computing IEEE Transactions on, vol. 7, no, 1, pp. 18-31, 2014. https://doi.org/10.1109/TSC.2012.27
  13. H. Al-Helal and R. Gamble, "Introducing replaceability into web service composition," Services Computing, IEEE Transactions on, vol. 7, no. 2, pp. 198-209, 2014. https://doi.org/10.1109/TSC.2013.23
  14. P. Leitner, W. Hummer, and S. Dustdar, "Cost-based optimization of service compositions," Services Computing, IEEE Transactions on, vol. 6, no. 2, pp. 239-251, 2013. https://doi.org/10.1109/TSC.2011.53
  15. B.Y. Wu, C.H. Chi, and S. Xu, "Service selection model based on qos reference vector," Services, 2007 IEEE Congress on, pp. 270-277, 2007.
  16. A. Klein, F. Ishikawa, and S. Honiden, "Towards network-aware service composition in the cloud," in Proc. of 21th International Conference on World Wide Web, France, pp. 959-968, 2012.
  17. Y. Liu, A.H. Ngu, and L.Z. Zeng, "Qos computation and policing in dynamic web service selection," in Proc. of 13th International World Wide Web Conference on Alternate Track Papers & Posters, pp.66-73, 2004.
  18. J. Xiao and R. Boutaba, "Qos-aware service composition and adaptation in autonomic communication," Selected Areas in Communications, IEEE Journal on, vol. 23, no. 12, pp.2344-2360, 2005. https://doi.org/10.1109/JSAC.2005.857212
  19. D. Wang, Y. Yang, and Z. Mi, "A genetic-based approach to web service composition in geo-distributed cloud environment," Computers & Electrical Engineering, vol. 43, pp. 129-141, 2015. https://doi.org/10.1016/j.compeleceng.2014.10.008