Journal of Intelligent Manufacturing

, Volume 25, Issue 2, pp 283–291 | Cite as

Towards an accurate evaluation of quality of cloud service in service-oriented cloud computing

  • Shangguang Wang
  • Zhipiao Liu
  • Qibo Sun
  • Hua Zou
  • Fangchun Yang
Article

Abstract

Cloud computing promises to provide high quality, on-demand services with service-oriented architecture. However, cloud service typically come with various levels of services and performance characteristics, which makes Quality of Cloud Service (QoCS) high variance. Hence, it is difficult for the users to evaluate these cloud services and select them to fit their QoCS requirements. In this paper, we propose an accurate evaluation approach of QoCS in service-oriented cloud computing. We first employ fuzzy synthetic decision to evaluate cloud service providers according to cloud users’ preferences and then adopt cloud model to computing the uncertainty of cloud services based on monitored QoCS data. Finally, we obtain the evaluation results of QoCS using fuzzy logic control. The simulation results demonstrate that our proposed approach can perform an accurate evaluation of QoCS in service-oriented cloud computing.

Keywords

Service-oriented cloud computing Cloud service QoCS Fuzzy synthetic decision Cloud model Fuzzy logic control 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adali M. R., Taskin M. F., Taskin H. (2009) Selecting the optimal shift numbers using fuzzy control model: a paint factory’s facility application. Journal of Intelligent Manufacturing 2: 267–272CrossRefGoogle Scholar
  2. Ardagna D., Pernici B. (2007) Adaptive service composition in flexible processes. IEEE Transactions on Software Engineering 33: 369–384CrossRefGoogle Scholar
  3. Chazalet, A. (2010a). Service level checking in the cloud computing context. In 3th IEEE international conference on cloud computing (pp. 297–304).Google Scholar
  4. Chazalet, A. (2010b). Service level agreements compliance checking in the cloud computing: architectural pattern, prototype, and validation. In 5th International conference on software engineering advances (pp. 184–189).Google Scholar
  5. Chuan D., Lin Y., Linru M., Yua C. (2011) Towards a practical and scalable trusted software dissemination system. Journal of Convergence 2: 53–60Google Scholar
  6. Chuang S. N., Chan A. T. S. (2008) Dynamic QoS adaptation for mobile middleware. IEEE Transactions on Software Engineering 34: 738–752CrossRefGoogle Scholar
  7. Dominguez-Sal D., Perez-Casany M., Larriba-Pey J. L. (2010) Cooperative cache analysis for distributed search engines. International Journal of Information Technology, Communications and Convergence 1: 41–65CrossRefGoogle Scholar
  8. Erginel N. (2010) Modeling and analysis of packing properties through a fuzzy inference system. Journal of Intelligent Manufacturing 6: 869–874CrossRefGoogle Scholar
  9. Ferretti, S., Ghini, V., Panzieri, F., Pellegrini, M., & Turrini, E. (2010). QoS-aware clouds. In 3th IEEE international conference on cloud computing (pp. 321–328).Google Scholar
  10. Freeman A. (1994) Fuzzy systems for control applications: The truck backer-upper. The Mathematica Journal 4: 64–69Google Scholar
  11. Ghosh, R., Trivedi, K. S., Naik, V. K., & Kim, D. S. (2010). End-to-end performability analysis for infrastructure-as-a-service cloud: An interacting stochastic models approach. In 16th IEEE Pacific Rim international symposium on dependable computing (pp. 125–132).Google Scholar
  12. Hoi, C., & Trieu, C. (2010). Ranking and mapping of applications to cloud computing services by SVD. In 1th IEEE/IFIP intenational workshops on network operations and management symposium (pp. 362–369).Google Scholar
  13. Hwang S. Y., Wang H., Tang J., Srivastava J. (2007) A probabilistic approach to modeling and estimating the QoS of web-services-based workflows. Information Sciences 177: 5484–5503CrossRefGoogle Scholar
  14. Jackson, K. R., Ramakrishnan, L., Muriki, K., Canon, S., Cholia, S., Shalf, J., et al. (2010). Performance analysis of high performance computing applications on the Amazon web services cloud. In IEEE second international conference on in cloud computing technology and science (pp. 159–168).Google Scholar
  15. Jeguirim S. E. G., Dhouib A. B., Sahnoun M., Cheikhrouhou M., Schacher L., Adolphe D. (2011) The use of fuzzy logic and neural networks models for sensory properties prediction from process and structure parameters of knitted fabrics. Journal of Intelligent Manufacturing 6: 873–884CrossRefGoogle Scholar
  16. Kryvinska N., Thanh D. V., Strauss C. (2010) Integrated management platform for seamless services provisioning in converged network. International Journal of Information Technology, Communications and Convergence 1: 77–91CrossRefGoogle Scholar
  17. Kuo Y. F., Chen P. C. (2006) Selection of mobile value-added services for system operators using fuzzy synthetic evaluation. Expert Systems with Applications 30: 612–620CrossRefGoogle Scholar
  18. Lee M., Yoon H., Shin H., Lee D. G. (2009) Intelligent dynamic workflow support for a ubiquitous Web service-based manufacturing environment. Journal of Intelligent Manufacturing 20: 295–302CrossRefGoogle Scholar
  19. Lee M., Lee J., Kim K., Park S. S. (2011) Evaluating service description to guarantee quality of U-service ontology. Journal of information Processing Systems 7: 287–298CrossRefGoogle Scholar
  20. Li D., Cheung D., Shi X., Ng V. (1998) Uncertainty reasoning based on cloud models in controllers. Computers and Mathematics with Applications 35: 99–123CrossRefGoogle Scholar
  21. Li, F., Yang, F., Shuang, K., & Su, S. (2008). A policy-driven distributed framework for monitoring quality of web services. In 6th IEEE international conference on web services (pp. 708–715).Google Scholar
  22. Lim H., Jang K., Kim B. (2010) A study on design and implementation of the ubiquitous computing environment-based dynamic smart on/off-line learner tracking system. Journal of Information Processing Systems 6: 609–620CrossRefGoogle Scholar
  23. Newton P. C., Arockiam L. (2011) A novel prediction technique to improve quality of service (QoS) for heterogeneous data traffic. Journal of Intelligent Manufacturing 6: 867–872CrossRefGoogle Scholar
  24. Oh S. (2010) New role-based access control in ubiquitous e-business environment. Journal of Intelligent Manufacturing 21: 607–612CrossRefGoogle Scholar
  25. Pei, L., Comerio, M., Maurino, A., & De Paoli, F. (2009). An approach to non-functional property evaluation of web services. In 7th IEEE international conference on web services (pp. 1004–1005).Google Scholar
  26. Pyshkin E., Kuznetsov A. (2010) Approaches for web search user interfaces: How to improve the search quality for various types of information. Journal of Convergence 1: 1–8Google Scholar
  27. Qi Y., Bouguettaya A. (2010) Computing service skyline from uncertain QoWS. IEEE Transactions on Services Computing 3: 16–29CrossRefGoogle Scholar
  28. Saaty T. L. (1980) The analytic hierarchy process. McGraw-Hill, New YorkGoogle Scholar
  29. Shangguang, W., Qibo, S., & Fangchun, Y. (2010). An approach for QoS measure of web service with multifactor support. In IEEE GLOBECOM workshops on web and pervaisve seccurity (pp. 1586–1590).Google Scholar
  30. Stantchev, V. (2009). Performance evaluation of cloud computing offerings. In 3th International conference on advanced engineering computing and applications in sciences (pp. 187–192).Google Scholar
  31. Van Broekhoven E., De Baets B. (2009) Only smooth rule bases can generate monotone Mamdani-Assilian models under center-of-gravity defuzzification. IEEE Transactions on Fuzzy Systems 17: 1157–1174CrossRefGoogle Scholar
  32. Wang R. C., Chang Y. C., Chang R. S. (2009) A semantic service discovery approach for ubiquitous computing. Journal of Intelligent Manufacturing 20: 327–335CrossRefGoogle Scholar
  33. Wang S. G., Sun Q. B., Yang F. C. (2010) Towards web service selection based on QoS estimation. International Journal of Web and Grid Services 6: 424–443CrossRefGoogle Scholar
  34. Yigitbasi, N., Iosup, A., Epema, D., & Ostermann, S. (2009). C-Meter: A framework for performance analysis of computing clouds. In 9th IEEE/ACM international symposium on cluster computing and the grid (pp. 472–477).Google Scholar
  35. Zadeh L. A. (1965) Fuzzy sets. Information and Control 8: 338–353CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Shangguang Wang
    • 1
  • Zhipiao Liu
    • 1
  • Qibo Sun
    • 1
  • Hua Zou
    • 1
  • Fangchun Yang
    • 1
  1. 1.State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijingChina

Personalised recommendations