Title: An intelligent-ranking framework for web services selection process

Authors: Alshaimaa Mustafa; Hany F. ElYamany; Mahmoud Elarabawy; Nashwa M. Yhiea; Hossam M. Faheem

Addresses: Mathematics Department, Faculty of Science, Suez Canal University, 4.5 Km, Ring Road, The New Campus, P.O. 41522, Ismailia, Egypt ' Computer Science Department, Faculty of Computers and Informatics, Suez Canal University, Elshiek Zaid Yourk, The Old Campus, P.O. 41522, Ismailia, Egypt ' Mathematics Department, Faculty of Science, Suez Canal University, 4.5 Km, Ring Road, The New Campus, P.O. 41522, Ismailia, Egypt ' Mathematics Department, Faculty of Science, Suez Canal University, 4.5 Km, Ring Road, The New Campus, P.O. 41522, Ismailia, Egypt ' Computers Organisation Department, Faculty of Computers and Information systems, Ain Shams University, Caliph Mamoun Street, Abassia Square, P.O. 11566, Cairo, Egypt

Abstract: This paper introduces an intelligent framework for selecting the best candidate service from the registered and published services within a particular registry through analysing the providers, the consumers and the registry constraints in addition to the business environment requirements. The proposed framework involves three particular phases conforming to the main structure of service-oriented architecture (SOA) which is the provider, consumer and registry. In each phase, an appropriate intelligent technique is deployed for establishing a particular functionality. Specifically, an intelligent agent technique is run at the provider's side for validating the encapsulated business within the designed WSs, a data mining model is executed at the registry's side for classifying the registered WSs with respect to their quality of services (QoS) parameters, and a statistical methodology which combines the registry and consumers' preferences is applied in order to recommend the best WS expected to operate properly with the target business process.

Keywords: web services; service-oriented architecture; SOA; quality of service; QoS; data mining; intelligent agents; statistical techniques; intelligent ranking; service selection.

DOI: 10.1504/IJSTM.2014.063566

International Journal of Services Technology and Management, 2014 Vol.20 No.1/2/3, pp.85 - 107

Available online: 17 Jul 2014 *

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