<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>To promote the practical use of web service technologies, it is critical to select a proper web service that will meet users’ preferences from a pool of web services with similar functions. It is usually a core issue during web service selection to describe and evaluate the quality of these web services. <italic>Average value</italic> can be employed to describe certain service quality and to evaluate the quality with multiple criteria through the <italic>Simple Additive Weight Method</italic>. Based on an analysis of various deficiencies in existing approaches proposed in some studies, four indicators were used: <italic>Price, Response Time, Reliability</italic> and <italic>Credibility</italic>. On top of that, recent sampling data sets were introduced to describe the uncertain quality of service (QoS) criteria; <italic>linear physical programming</italic> was used to evaluate QoS with comprehensive criteria to meet the need to objectively describe uncertain QoS criteria, and preference regions were set to adapt to interval characteristics of criteria. Finally, a computational example is provided to demonstrate the feasibility and effectiveness of the method.</p>
</abstract>

To promote the practical use of web service technologies, it is critical to select a proper web service that will meet users’ preferences from a pool of web services with similar functions. It is usually a core issue during web service selection to describe and evaluate the quality of these web services. Average value can be employed to describe certain service quality and to evaluate the quality with multiple criteria through the Simple Additive Weight Method. Based on an analysis of various deficiencies in existing approaches proposed in some studies, four indicators were used: Price, Response Time, Reliability and Credibility. On top of that, recent sampling data sets were introduced to describe the uncertain quality of service (QoS) criteria; linear physical programming was used to evaluate QoS with comprehensive criteria to meet the need to objectively describe uncertain QoS criteria, and preference regions were set to adapt to interval characteristics of criteria. Finally, a computational example is provided to demonstrate the feasibility and effectiveness of the method.

Study of a linear-physical-programming-based approach for web service selection under uncertain service quality

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

To promote the practical use of web service technologies, it is critical to select a proper web service that will meet users’ preferences from a pool of web...

Study of a linear-physical-programming-based approach for web service selection under uncertain service quality

Data publikacji: 29 kwi 2022

Zakres stron: 2393 - 2404

Otrzymano: 09 wrz 2021

Przyjęty: 23 sty 2022

DOI: https://doi.org/10.2478/amns.2021.2.00177

Słowa kluczowe
web service, quality of service, web service selection, linear physical programming, uncertain service quality

© 2023 Jian Yu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Fig. 2

Study of a linear-physical-programming-based approach for web service selection under uncertain service quality

Data publikacji: 29 kwi 2022

Zakres stron: 2393 - 2404

Otrzymano: 09 wrz 2021

Przyjęty: 23 sty 2022

DOI: https://doi.org/10.2478/amns.2021.2.00177

Słowa kluczoweweb service, quality of service, web service selection, linear physical programming, uncertain service quality

© 2023 Jian Yu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Fig. 2

Słowa kluczowe
web service, quality of service, web service selection, linear physical programming, uncertain service quality