Study on service selection effort estimation in service oriented architecture-based applications powered by information entropy weight fuzzy comprehensive evaluation model

Service selection is a very challenging core task in service oriented architecture-based application (SOABA) development. Service selection is based on user's business need and budget available. A large amount of effort is invested in selecting the most preferred service from a pool of similar services available in the market by various service providers. To propose a direction for solving the problem of service selection effort (SSE) estimation in SOABA is the objective in this study. An algorithm for SSE estimation powered by information entropy weight (IEW) fuzzy comprehensive evaluation model is presented in this study wherein the synthesis performance of each candidate service is evaluated to select the most preferred service. Larger the synthesis performance of a candidate service, higher the chances of its selection and less will be the effort invested. An empirical study is presented that assess the 24 significant parameters that affect SSE estimation by using proposed algorithm. This approach is comprehensible and rational and well suited for SOABA. The results obtained via this proposed method suggest its applicability and usefulness for real-world applications. The proposed work also explains why IEW method is useful for SSE estimation along with the research gap in existing common evaluation methods.