Skyline-based models for Web Services Selection
Skyline Models and Algorithms for Web Services Selection Based on Invocation History
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With the proliferation of service-oriented architectures (SOA), the number of Web services has increased dramatically, making it difficult for users to select a relevant service. The Skyline paradigm, which helps select Web services based on Quality of Service (QoS) data, has become popular by presenting only non-dominated services. However, this approach has limitations, such as producing incomparable results, giving equal weight to all QoS criteria, and being unable to control the size of the results.This book proposes several approaches to overcome these challenges. The first, SkyAP-S3, com...
With the proliferation of service-oriented architectures (SOA), the number of Web services has increased dramatically, making it difficult for users to select a relevant service. The Skyline paradigm, which helps select Web services based on Quality of Service (QoS) data, has become popular by presenting only non-dominated services. However, this approach has limitations, such as producing incomparable results, giving equal weight to all QoS criteria, and being unable to control the size of the results.This book proposes several approaches to overcome these challenges. The first, SkyAP-S3, combines multi-criteria methods (MCDM) such as Skyline, AHP to weight criteria, and PROMETHEE to integrate user preferences. The second, SEFAP, enhances SkyAP-S3 by handling uncertainty in user judgments, using entropy and Fuzzy AHP. Finally, an advanced version of Fuzzy AHP is proposed to automate the comparison of criteria and services via a discretization algorithm. Experiments have demonstrated the effectiveness of these approaches.
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