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Employing Relevance Feedback to Embed Content and Service Importance into the Selection Process of Composite Cloud Services

  • Dimosthenis Kyriazis
  • Nikolaos Doulamis
  • George Kousiouris
  • Andreas Menychtas
  • Marinos Themistocleous
  • Vassilios C. Vescoukis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9512)

Abstract

Cloud computing is essentially changing the way services are built, provided and consumed. As a paradigm building on a set of combined technologies, it enables service provision through the commoditization of IT assets and on-demand usage patterns. In the emerging era of the Future Internet, clouds aim at facilitating applications that move away from the monolithic approach into an Internet-scale one, thus exploiting information, individual offerings and infrastructures as composite services. In this paper we present an approach for selecting the services (that comprise the composite ones) in order to meet the end-to-end Quality of Service (QoS) requirements. The approach is enhanced with a relevance feedback mechanism that provides additional information with respect to the importance of the content and the service. The latter is performed in an automated way, allowing for user preferences to be considered during the service selection process. We also demonstrate the operation of the implemented approach and evaluate its effectiveness using a real-world scenario, based on a computer vision application.

Keywords

Cloud computing Quality of service Composite services Relevance feedback 

Notes

Acknowledgements

The publication of this paper has been partly supported by the University of Piraeus Research Center, and by the European Community under grant agreements n° 214777 (IRMOS project) and n° 216465 (SCOVIS project).

References

  1. 1.
    Papazoglou, M.P., Georgakopoulos, D.: Service-oriented computing. In: Communications of the ACM (2003)Google Scholar
  2. 2.
    Future Internet Architecture (FIArch) Group: Future Internet Design Principles. European Commission (2012). http://ec.europa.eu/information_society/activities/foi/docs/fiarchdesignprinciples-v1.pdf
  3. 3.
    IBM White Paper: The Benefits of Cloud Computing: A New Era of Responsiveness, Effectiveness and Efficiency in IT Service Delivery (2009)Google Scholar
  4. 4.
    Kyriazis, D.: Cloud computing service level agreements–exploitation of research results. Technical report, European Commission, Brussels (2013). http://ec.europa.eu/digital-agenda/en/news/cloud-computing-service-level-agreements-exploitation-research-results
  5. 5.
    Doulamis, A.: Fair QoS resource management and non-linear prediction of 3D rendering applications. In: IEEE International Symposium on Circuits & Systems, Vancouver, Canada (2004)Google Scholar
  6. 6.
    Zilci, B.I., Slawik, M., Küpper, A.: Cloud service matchmaking using constraint programming. In: IEEE International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (2015)Google Scholar
  7. 7.
    Zeng, L., Benatallah, B., Ngu, A.H., Dumas, M., Kalagnanam, J., Chang, H.: QoS-aware middleware for web services composition. IEEE Trans. Softw. Eng. 30, 311–327 (2004)CrossRefGoogle Scholar
  8. 8.
    Ardagna, D., Pernici, B.: Adaptive service composition in flexible processes. IEEE Trans. Softw. Eng. 33(6), 369–384 (2007)CrossRefGoogle Scholar
  9. 9.
    Zeng, L., Benatallah, B., Dumas, M., Kalagnanam, J., Sheng, Q.Z.: Quality driven web services composition. In: International Conference on World Wide Web, Hungary (2003)Google Scholar
  10. 10.
    Berbner, R., Spahn, M., Repp, N., Heckmann, O., Steinmetz, R.: Heuristics for QoS-aware web service composition. In: IEEE International Conference on Web Services, USA (2006)Google Scholar
  11. 11.
    Alrifai, M., Skoutas, D., Risse, T.: Selecting skyline services for QoS-based web service composition. In: International Conference on World Wide Web, USA (2010)Google Scholar
  12. 12.
    Alrifai, M., Risse, T.: Combining global optimization with local selection for efficient QoS-aware service composition. In: International Conference on World Wide Web, Madrid, Spain (2009)Google Scholar
  13. 13.
    Sun, Q., Wang, S., Zou, H., Yang, F.: QSSA: a QoS-aware service selection approach. Int. J. Web Grid Serv. 7(2), 147–169 (2011)CrossRefGoogle Scholar
  14. 14.
    Yu, T., Zhang, Y., Lin, K.J.: Efficient algorithms for web services selection with end-to-end QoS constraints. ACM Trans. Web (2007)Google Scholar
  15. 15.
    Zhao, S., Chen, G., Chen, H.: Reputation-aware Service Selection based on QoS Similarity. J. Netw. (2011). Academy PublishersGoogle Scholar
  16. 16.
    Rui, Y., Huang, T.S., Ortega, M., Mehrotra, S.: Relevance feedback: a power tool for interactive content-based image retrieval. IEEE Trans. Circ. Syst. Video Technol. 8(5), 644–655 (1998)CrossRefGoogle Scholar
  17. 17.
    Doulamis, A., Avrithis, Y., Doulamis, N., Kollias, S.: Interactive content-based retrieval in video databases using fuzzy classification and relevance feedback. In: IEEE International Conference on Multimedia Computing and Systems, Florence, Italy (1999)Google Scholar
  18. 18.
    Wang, X.Y., Zhang, B.B., Yang, H.Y.: Active SVM-based relevance feedback using multiple classifiers ensemble and features reweighting. Eng. Appl. Artif. Intell. (2012)Google Scholar
  19. 19.
    Zhang, L., Wang, L., Lin, W.: Semisupervised biased maximum margin analysis for interactive image retrieval. IEEE Trans. Image Process. 21(4), 2294–2308 (2012)MathSciNetCrossRefGoogle Scholar
  20. 20.
    Zhang, L., Wang, L., Lin, W.: Generalized biased discriminant analysis for content-based image retrieval. IEEE Trans. Syst. Man Cybern. (2012)Google Scholar
  21. 21.
    Doulamis, A., Tziritas, G.: Content-based low adaptation in low/variable bandwidth communication networks using adaptable neural networks structures. In: IEEE International Joint Conference on Neural Networks (2006)Google Scholar
  22. 22.
    Katsaros, G., Kousiouris, G., Gogouvitis, S., Kyriazis, D., Menychtas, A., Varvarigou, T.: A self-adaptive hierarchical monitoring mechanism for clouds. J. Syst. Softw. (2012). ElsevierGoogle Scholar
  23. 23.
    Gogouvitis, S., Konstanteli, K., Waldschmidt, S., Kousiouris, G., Katsaros, G., Menychtas, A., Kyriazis, D., Varvarigou, T.: Workflow management for soft real-time interactive applications in virtualized environments. Future Gener. Comput. Syst. (2012)Google Scholar
  24. 24.
    Papoulis, A.: Probability, Random Variables, and Stochastic Processes. McGraw Hill, New York (1984)zbMATHGoogle Scholar
  25. 25.
    Doulamis, N., Doulamis, A.: Evaluation of relevance feedback in content-based in retrieval systems. Sig. Process. Image Commun. (2006)Google Scholar
  26. 26.
    Voulodimos, A., Kosmopoulos, D., Vasileiou, G., Sardis, E., Anagnostopoulos, V., Lalos, C., Doulamis, A., Varvarigou, T.: A threefold dataset for activity and workflow recognition in complex industrial environments. IEEE Multimedia 19(3), 42–52 (2012)CrossRefGoogle Scholar
  27. 27.
    Voulodimos, A., Kosmopoulos, D., Vasileiou, G., Sardis, E., Doulamis, A., Anagnostopoulos, V., Lalos, C., Varvarigou, T.: Dataset for workflow recognition in industrial scenes. In: IEEE International Conference on Image Processing, Brussels (2011)Google Scholar
  28. 28.
    Xiang, T., Gong, S., Parkinson, D.: Autonomous visual events detection and classification without explicit object centred segmentation and tracking. In: British Machine Vision Conference, pp. 233–242 (2002)Google Scholar
  29. 29.
    Kyriazis, D., Menychtas, A., Kousiouris, G., Oberle, K., Voith, T., Boniface, M., Oliveros, E., Cucinotta, T., Berger, S.: A real-time service oriented infrastructure. GSTF Int. J. Comput. (2011)Google Scholar
  30. 30.
    Rui, Y., Huang, T.S.: Optimizing learning in image retrieval. In: IEEE International Conference on Computer Vision and Pattern Recognition (2000)Google Scholar
  31. 31.
    Cloud Computing Expert Group Report. The Future of Cloud Computing. European Commission (2010). http://cordis.europa.eu/fp7/ict/ssai/docs/cloud-report-final.pdf

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Dimosthenis Kyriazis
    • 1
  • Nikolaos Doulamis
    • 2
  • George Kousiouris
    • 2
  • Andreas Menychtas
    • 2
  • Marinos Themistocleous
    • 1
  • Vassilios C. Vescoukis
    • 2
  1. 1.Department of Digital SystemsUniversity of PiraeusPiraeusGreece
  2. 2.National Technical University of AthensAthensGreece

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