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Classifying Web Services based on QoS Parameters using Extended Dataset

International Journal of Computer Applications
© 2013 by IJCA Journal
Volume 74 - Number 8
Year of Publication: 2013
Vandan Tewari
Urjita Thakar
Nirmal Dagdee

Vandan Tewari, Urjita Thakar and Nirmal Dagdee. Article: Classifying Web Services based on QoS Parameters using Extended Dataset. International Journal of Computer Applications 74(8):33-36, July 2013. Full text available. BibTeX

	author = {Vandan Tewari and Urjita Thakar and Nirmal Dagdee},
	title = {Article: Classifying Web Services based on QoS Parameters using Extended Dataset},
	journal = {International Journal of Computer Applications},
	year = {2013},
	volume = {74},
	number = {8},
	pages = {33-36},
	month = {July},
	note = {Full text available}


Web Services are the interoperable and loosely coupled components for simplifying business processes over the web and are popular model of distributed computing now a days. There are a very few datasets available regarding Quality of Service (QoS) for web services since web services datasets are difficult to create. The reason being that it requires more effort to collect service information from various sources and structure it into a dataset. QWS dataset [5] is a data set which contains quality of service parameters for Web Services. However, this dataset includes only nine quality of service parameters and misses on some very important non-functional attributes such as security, interoperability and robustness which may be important while discovering web services which are sensitive in nature. This constitutes the class of services used for defense applications related to national security and service related to heavy financial transactions. In this paper, a method of web service classification has been proposed based on QoS Parameters of web services. Additionally an extended QoS parameters data set has been created using statistical techniques and concept of Highly Normalized Function. This extended dataset consists of unlabeled samples, which are processed to generate labeled dataset. This synthetic dataset has been named as Non-functional Parameters Dataset (NfPD).


  • Jaideep Roy and Anupama Ramanujan, "Understanding Web Services", 2001 IEEE
  • XML http://www. w3schools. com/xml/default. asp
  • Web Services www. w3schools. com/webservices/ws_intro. asp
  • SOAP Version 1. 2 Part 0: Primer W3C Recommendation 24 June 2003, Available at: http://www. w3. org/TR/soap12-part0/, Accessed on06/04/2013.
  • Universal Description Discovery and Integration (UDDI) Version 3. 0. 2 at:http://www. uddi. org/pubs/uddi_v3. htm,
  • Data Mining, en. wikipedia. org/wiki/Data_mining?
  • Matthias Seeger, "Learning with labeled and unlabeled data", Institute for Adaptive and Neural Computation, University of Edinburgh
  • Eyhab AL-Masri and Qusay H. Mahmoud, "Towards Quality-Driven Web Service Discovery", University of Guelph, 2008 IEEE
  • Service Oriented Architecture http://java. sun. com/developer/Books/j2ee/jwsa/JWSA_CH02. pdf www. service-architecture. com/web-services/articles/
  • Jeffrey W. Seifert, "Data Mining: An Overview", Analyst in Information Science and Technology Policy Resources, Science, and Industry Division
  • Vandan Tewari, Nirmal Dagdee and Aruna Tiwari. Article: User Oriented Web Services Discovery based on QoS Parameters in Multiple Registries. International Journal of Computer Applications 46(24):8-12, May 2012. Published by Foundation of Computer Science, New York, USA
  • Al-Masri, E. , and Mahmoud, Q. H. , "Discovering the best web service", (poster) 16th International Conference on World Wide Web (WWW), 2007, pp. 1257-1258
  • Al-Masri, E. , and Mahmoud, Q. H. , "QoS-based Discovery and Ranking of Web Services", IEEE 16th International Conference on Computer Communications and Networks (ICCCN), 2007, pp. 529-534.
  • Hassan Reza, Dan Jurgens, Jamie White, Jason Anderson, and Jay Peterson, "An Architectural Design Selection Tool Based on Design Tactics, Scenarios and Nonfunctional Requirements", University of North Dakota, EPSCoR NASA grant #NCC5-582