Evaluating Web Service QoE by Learning Logic Networks

Natalia Kushik, Nina Yevtushenko, Ana Cavalli, Wissam Mallouli, Jeevan Pokhrel

Abstract

This paper is devoted to the problem of evaluating the quality of experience (QoE) for a given web service based on the values of service parameters (for instance, QoS indicators). Different self-learning algorithms can be used to reach this purpose. In this paper, we propose to use self-learning logic networks, called also circuits, for evaluating the QoE of web services, since modern software tools can efficiently deal with very large logic networks. As usual, for machine learning techniques, statistics are used to design the initial circuit that accepts service parameter values as inputs and produces the QoE value as an output. The circuit is self-adaptive, i.e., when a new end-user provides a feedback of the service satisfaction the circuit is resynthesized in order to behave properly (if needed). Such resynthesis (circuit learning) can be efficiently performed using a number of tools for logic synthesis and verification.

References

  1. Ahmed, S., Begum, M., Hasan Siddiqui, F., Abul Kashem, M., 2012. Dynamic Web Service Discovery Model Basedon Artificial Neural Network with QoS Support. International Journal of Scientific & Engineering Research Volume 3, Issue 3, pp. 1-7.
  2. Al-Masri, E., Mahmoud Qusay, H., 2009. Discovering the Best Web Service: A Neural Network-based Solution. SMC 2009, pp. 4250-4255.
  3. Booth, D., Haas, H., McCabe, F., Newcomer, E., Champion, M., Ferris, C., Orchard, D., 2004. Web services architecture. W3C Working Group Note, W3C Technical Reports and Publications, url: http://www.w3.org/TR/ws-arch/.
  4. Khirman, S., Henriksen, P., 2002. Relationship between Quality-of-Service and Quality-of-Experience for public Internet service. In Proc.of PAM 2002.
  5. Kim, H. J., Lee, D. H., Lee, J. M., Lee, K. H., Lyu, W., Choi S.G., 2008. The QoE evaluation method through the QoS-QoE correlation model. In Proc. of NCM 08, vol. 2, pp. 719-725.
  6. Kuehlmann, A. (ed.), 2003. The Best of ICCAD. 20 Years of Excellence in Computer-Aided Design. Kluwer Academic Publishers.
  7. Lin, M., Xie, J., Guo, H., Wang, H., 2005. Solving QoSdriven web service dynamic composition as fuzzy constraint satisfaction. EEE 2005, pp. 9-14.
  8. McCluskey, E. J., 1965. Introduction to the theory of switching circuits. McGraw-Hill Book Company, NY.
  9. Mitchell, T.M., 1997. Machine learning. McGraw Hill series in computer science, McGraw-Hill.
  10. Morais, A., Cavalli, A., 2012. Deliverable D2.1 - State of the art of SQM/CEM technology, tools, and standartization. IPNQSYS European project, url: http://projects.celtic-initiative.org/ipnqsis/IPNQSISD21.pdf.
  11. Pokhrel, J., Mallouli, W., Montes de Oca, E., 2013. QoE Prediction and Self-Learning Mechanisms. Technical report on the PIMI Project.
  12. Torres, R., Astudillo, H., Salas, R., 2011. Self-Adaptive Fuzzy QoS-Driven Web Service Discovery. In IEEE SCC 2011, pp. 64-71.
  13. Winckler, M. A., Bach, C., Bernhaupt, R., 2013. Identifying user experience dimensions for mobile incident reporting in urban contexts. IEEE Transactions on Communications, vol. 56, no. 2, pp. 40-82.
  14. Zadeh, L. A., 1965. Fuzzy sets. Information and Control, 8 (3), pp. 338-353.
Download


Paper Citation


in Harvard Style

Kushik N., Yevtushenko N., Cavalli A., Mallouli W. and Pokhrel J. (2014). Evaluating Web Service QoE by Learning Logic Networks . In Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-023-9, pages 168-176. DOI: 10.5220/0004855801680176


in Bibtex Style

@conference{webist14,
author={Natalia Kushik and Nina Yevtushenko and Ana Cavalli and Wissam Mallouli and Jeevan Pokhrel},
title={Evaluating Web Service QoE by Learning Logic Networks},
booktitle={Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2014},
pages={168-176},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004855801680176},
isbn={978-989-758-023-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - Evaluating Web Service QoE by Learning Logic Networks
SN - 978-989-758-023-9
AU - Kushik N.
AU - Yevtushenko N.
AU - Cavalli A.
AU - Mallouli W.
AU - Pokhrel J.
PY - 2014
SP - 168
EP - 176
DO - 10.5220/0004855801680176