Quality Assessment of Web Services Using Soft Computing Techniques


  • V Mohan Patro Department of Computer Science Berhampur University Berhampur, Odisha INDIA - 760007
  • Bonomali Khuntia
  • Manas Ranjan Patra




Web services, Quality of Services (QoS), Backpropagation, Continuous Genetic Algorithm


With the ever growing number of web services in the Internet the selection of a suitable web service has become a mind boggling task. Several quality parameters are being considered for a judicious selection of a web service in a given service context. One of the popular measures for classifying web services is the use of Web Service Relevance Function (WSRF). A number of classifiers have been used which have yielded accuracy up to 99% considering WSRF as one of the attributes of QWS dataset.  But, the maximum accuracy achieved by any classifier without WSRF is only 89.99%. In this paper, a feed-forward backpropagation neural network (BPNN) with adaptive momentum factor has been employed to further improve the accuracy. Furthermore, a similar neural network is modelled for determining the WSRF of the web services included in the QWS dataset. As an alternative, Genetic Algorithm is used to find the weight factors associated with each parameter to calculate WSRF, assuming it to be a linear function of those parameters. The average errors for WSRF per pattern obtained in the two approaches are 1.0447 and 1.176 respectively. These calculated WSRF values can be used for classification to enhance the accuracy of a classifier.


Jinghai Rao and Xiaomeng Su., “A Survey of Automated Web Service Composition Methods”, Lecture Notes in Computer Science, 2005, Volume 3387/2005, 43-54.

S.Susila and S.Vadivel, “Web service Selection through QoS agent Web service”, IJSWS 13-325; © 2013, pp.18-23.

Ramakanta Mohanty, V. Ravi and M.R. Patra, “Web-services classification using intelligent techniques”, Elsevier, Expert Systems with Applications 37 (2010), pp. 5484–5490.

LI Yuan-jie and CAO Jian, “Web Service Classification Based on Automatic Semantic Annotation and Ensemble Learning”, 2012, IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum, 2274-2279.

Ramakanta Mohanty, V. Ravi and M. R. Patra, “Classification of Web Services Using Bayesian Network”, Journal of Software Engineering and Applications, 2012, 5, 291-296.

L. Ai and M. Tang, “A hybrid genetic algorithm for the optimal constrained web service selection problem in web service composition”, IEEE Congress on Evolutionary Computation, Barcelona, Spain, 2010, 8 pages.

E. Maximilien and M. Singh, “A framework and ontology for dynamic Web services selection” IEEE Internet Computing, vol. 8, no. 5, pp. 84–93, Sept.-Oct. 2004.

K. Verma, R. Akkiraju, R. Goodwin, P. Doshi, and J. Lee, “On accommodating inter service dependencies in web process flow composition,” in Proc. AAAI Spring Symposium on SWS, 2004, pp. 37–43.

G. Canfora, M. Di Penta, R. Esposito, and M. L. Villani, “An approach for QoS-aware service composition based on genetic algorithms”, In Proc. of the 2005 conference on Genetic and evolutionary computation., New York, NY, USA: ACM, 2005, pp. 1069–1075.

D. Ardagna and B. Pernici, “Adaptive service composition in flexible processes”, IEEE Transactions on Software Engineering, vol. 33, no. 6, pp. 369–384, June 2007.

Yu, T., Zhang, Y., and Lin, K.J., 2007, “Efficient algorithms for Web services selection with end-to-end QoS constraints”, ACM Trans. Web 1, 1, Article 6 (May 2007), 26 pages.

Xu, Z.; Martin, P.; Powley, W. and Zulkernine, F.; “Reputation-Enhanced QoS-based Web Services Discovery”, 2007, Proceedings of IEEE International Conference on Web Services. Salt Lake City, USA, pp. 249-256.

Al-Masri, E. and Mahmoud, Q., 2007, “Discovering the Best Web Service”, Proceeding of the 16th international conference on World Wide Web. Banff, Canada, pp. 1257-1258.

Petrova-Antonova, Dessislava., "A qos-aware approach for web service selection based on probability evaluation", M CC SSI MCCSIS (2011): 43.

M. Kamalahhasan, “Applications of Neural Networks for Ranking of Web Services using QoS Metrics”, SSRG International Journal of Electronics and Communication Engineering (SSRG-IJECE) – volume 1, Issue 1–Feb 2014, pp. 4-8.

Eyhab Al-Masri and Qusay H. Mahmoud, “Discovering the Best Web Service: A Neural Network-based Solution”, Proceedings of the 2009 IEEE International Conference on Systems, Man, and Cybernetics San Antonio, TX, USA - October 2009, 4250-4255.

Al-Masri, E., and Mahmoud, Q. H., "QoS-based Discovery and Ranking of Web Services", IEEE, 2007, pp.529-534




How to Cite

Patro, V. M., Khuntia, B., & Patra, M. R. (2015). Quality Assessment of Web Services Using Soft Computing Techniques. Discoveries in Agriculture and Food Sciences, 3(1), 59. https://doi.org/10.14738/tnc.31.958