Open AccessUsing Ensemble and TOPSIS with AHP for Classification and Selection of Web Services
Author(s) -
Mithilesh Kumar Pandey,
Sunita Jalal,
Chetan Singh Negi,
Dharmendra Kumar Yadav
Publication year - 2021
Publication title -
vietnam journal of computer science
Language(s) - English
Resource type - Journals
eISSN - 2196-8888
pISSN - 2196-8896
DOI - 10.1142/s2196888822500130
Subject(s) - computer science , web service , analytic hierarchy process , topsis , preprocessor , web intelligence , data mining , quality of service , ideal solution , web modeling , world wide web , artificial intelligence , operations research , engineering , computer network , physics , thermodynamics
Due to the increasing number of Web Services with the same functionality, selecting a Web Service that best serves the needs of the Web Client has become a tremendously challenging task. Present approaches use non-functional parameters of the Web Services but they do not consider any preprocessing of the set of functionally Similar Web Services. The lack of preprocessing results in increased use of computational resources due to unnecessary processing of Web Services that have a very low to no chance of satisfying the consumer’s requirements. In this paper, we propose an Ensemble classification method for preprocessing and a Web Service Selection method based on the Quality of Service (QoS) parameters. Once the most eligible Web Services are enumerated through classification, they are ranked using the Technique of Order Preference by Similarity to Ideal Solution (TOPSIS) method with Analytic Hierarchy Process (AHP) used for weight calculation. A prototype of the method is developed, and experiments are conducted on a real-world Web Services dataset. Results demonstrate the feasibility of the proposed method.