A Classification Based Web Service Selection Approach

Selection of an appropriate web service fulfilling the requirements of the end user is a challenging task. Most of the existing systems use Quality of Service (QoS) as predominant parameter for web service selection, without any preprocessing or filtering. These systems consider all of the candidate web services during selection process and require unnecessary processing of those web services which are far below the expectations of the end user. In this work, an approach for web service selection based on QoS parameters is proposed. The proposed method starts with prefiltering of candidate web services using classification technique. An improved PROMETHEE method, we call it as PROMETHEE Plus, is applied to most eligible web services and Maximizing Deviation Method based hybrid weight evaluation mechanism is adopted. Top-k web services matching closely with the QoS requirements of the end user are selected. Experiments on the dataset of real world web services are conducted. Experimental results show that our approach performs better in terms of end user satisfaction and efficiency with reference to the existing similar approaches.

[1]  Athman Bouguettaya,et al.  Web Service Classification Using Support Vector Machine , 2010, 2010 22nd IEEE International Conference on Tools with Artificial Intelligence.

[2]  Chen Ding,et al.  User-centered design of a QoS-based web service selection system , 2011, Service Oriented Computing and Applications.

[3]  Donald Kossmann,et al.  The Skyline operator , 2001, Proceedings 17th International Conference on Data Engineering.

[4]  Eyhab Al-Masri,et al.  QoS-based Discovery and Ranking of Web Services , 2007, 2007 16th International Conference on Computer Communications and Networks.

[5]  Qi Yu,et al.  An LDA-SVM Active Learning Framework for Web Service Classification , 2016, 2016 IEEE International Conference on Web Services (ICWS).

[6]  Fulian Yin,et al.  Combination Weighting Method Based on Maximizing Deviations and Normalized Constraint Condition , 2016 .

[7]  Zakaria Maamar,et al.  On the Analysis of Satisfaction for Web Services Selection , 2012, 2012 IEEE Ninth International Conference on Services Computing.

[8]  Ping-Feng Pai,et al.  An Integrated Methodology using Linguistic PROMETHEE and Maximum Deviation Method for Third-party Logistics Supplier Selection , 2010, Int. J. Comput. Intell. Syst..

[9]  Dmitry Podkopaev,et al.  Simple additive weighting - A metamodel for multiple criteria decision analysis methods , 2016, Expert Syst. Appl..

[10]  San-Yih Hwang,et al.  Service Selection for Web Services with Probabilistic QoS , 2015, IEEE Transactions on Services Computing.

[11]  Xumin Liu,et al.  Personalized Decision-Strategy based Web Service Selection using a Learning-to-Rank Algorithm , 2015, IEEE Transactions on Services Computing.

[12]  Ping Wang,et al.  QoS-aware web services selection with intuitionistic fuzzy set under consumer's vague perception , 2009, Expert Syst. Appl..

[13]  Alejandro Zunino,et al.  Case-based Reasoning for Web Service Discovery and Selection , 2016, CLEI Selected Papers.

[14]  Yue Tan,et al.  QoS Browsing for Web Service Selection , 2009, ICSOC/ServiceWave.

[15]  Jiri Matas,et al.  On Combining Classifiers , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Yue Wang,et al.  A skyline-based efficient web service selection method supporting frequent requests , 2016, 2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design (CSCWD).

[17]  Jie Yang,et al.  Semi-automatic Web Service Classification Using Machine Learning , 2015 .

[18]  Caroline Herssens,et al.  Dealing with Quality Tradeoffs during Service Selection , 2008, 2008 International Conference on Autonomic Computing.

[19]  Fatma Rhimi,et al.  Enhancing Skyline Computation with Collaborative Filtering Techniques for QoS-Based Web Services Selection , 2015, 2015 IEEE 14th International Symposium on Network Computing and Applications.

[20]  Eyhab Al-Masri,et al.  Discovering the best web service , 2007, WWW '07.

[21]  Ohbyung Kwon,et al.  A complementary ubiquitous service bundling method using service complementarity index , 2011, Expert Syst. Appl..

[22]  Han-Gyu Ko,et al.  Adaptive Service Selection According to the Service Density in Multiple Qos Aspects , 2016, IEEE Transactions on Services Computing.

[23]  Eyhab Al-Masri,et al.  Discovering the best web service: A neural network-based solution , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[24]  Jaap Gordijn,et al.  Dynamic Cluster-based Service Bundling: A Value-oriented Framework , 2011, 2011 IEEE 13th Conference on Commerce and Enterprise Computing.

[25]  Sandeep Kumar,et al.  Cognition based Service Selection in Semantic Web Service Composition , 2008 .

[26]  Sandeep Kumar,et al.  Web Service Selection using Semantic Matching , 2016 .

[27]  Stephen S. Yau,et al.  QoS-Based Service Ranking and Selection for Service-Based Systems , 2011, 2011 IEEE International Conference on Services Computing.

[28]  Zibin Zheng,et al.  QoS-Aware Web Service Recommendation by Collaborative Filtering , 2011, IEEE Transactions on Services Computing.

[29]  Nikos E. Mastorakis,et al.  Novel models for multi-agent negotiation based semantic web service composition , 2010 .

[30]  Hala A. Effat,et al.  Mapping potential landfill sites for North Sinai cities using spatial multicriteria evaluation , 2012 .

[31]  Jean Pierre Brans,et al.  A PREFERENCE RANKING ORGANIZATION METHOD , 1985 .

[32]  Manas Ranjan Patra,et al.  Web-services classification using intelligent techniques , 2010, Expert Syst. Appl..

[33]  Manas Ranjan Patra,et al.  Classification of Web Services using Fuzzy Classifiers with Feature Selection and Weighted Average Accuracy , 2015 .

[34]  Jaap Gordijn,et al.  Value-Based Service Bundling: A Customer-Supplier Approach , 2011, 2011 IEEE 15th International Enterprise Distributed Object Computing Conference Workshops.

[35]  Hwa-Young Jeong,et al.  Best Web Service Selection Based on the Decision Making Between QoS Criteria of Service , 2005, ICESS.

[36]  Athman Bouguettaya,et al.  Multi-attribute optimization in service selection , 2011, World Wide Web.

[37]  Wolfgang Nejdl,et al.  A hybrid approach for efficient Web service composition with end-to-end QoS constraints , 2012, TWEB.