Trusted Service by Enhancing Wi-Fi Service Quality Assessment with User Feedback Integration: A Cloud Theory-Based Approach

In the dynamic field of fog computing, there is a clear trend toward exploiting local, resource-rich nodes to bypass traditional cloud infrastructure limitations. This study introduces an innovative method for enhancing the reliability of Wi-Fi systems, crucial in fog computing, by integrating quality-focused user feedback. Our approach significantly enhances the assessment of Wi-Fi system trustworthiness by emphasizing user perspectives. While traditional metrics such as Availability, Performance, and Security Parameters are crucial for defining Quality of Service (QoS), our research also integrates user feedback as a key, albeit secondary, factor in assessing Wi-Fi node trustworthiness. Designed to improve the evaluation process, this method combines system-generated QoS metrics with user feedback to subtly increase trust assessment objectivity. This not only connects technical service quality with user experiences but also strengthens trust and reliability in fog computing. Utilizing sophisticated cloud theory techniques, our model employs both backward and forward cloud generators — the backward generator converts QoS data into qualitative insights, while the forward generator combines these insights with user feedback to thoroughly evaluate Wi-Fi node service quality. The integration of user feedback allows for a more dynamic and responsive system evaluation, addressing the limitations of previous models by providing a comprehensive assessment that aligns technical service quality with user experiences. This enhancement in trust evaluation is achieved by skillfully blending QoS metrics and user feedback to create a more objective trust value.