Quality of Experience for Interactive Web Applications
|Title:||Quality of Experience for Interactive Web Applications||Authors:||ZolghadriJahromi, Hamed||Permanent link:||http://hdl.handle.net/10197/12813||Date:||2020||Online since:||2022-04-29T15:10:17Z||Abstract:||The increasing adoption of web applications for personal and business use has motivated service providers to better understand the factors that influence the Quality of Experience (QoE) from a user's perspective. Understanding and quantifying Web QoE helps providers to be aware of the end-users perceived quality and can point towards areas to improve. Users have expectations with respect to the time it takes to execute and respond to an interaction with a web application. Waiting time has been confirmed to have a significant impact on user satisfaction. Various waiting-time-based metrics have been developed and used in Web QoE models to estimate the quality experienced by end-users. Web application developers have been actively introducing innovative interactive features such as animated content and immersive media to their applications, aiming to capture the users' attention and improve the functionality and utility of the web applications. As a result, web applications have become complex entities and QoE estimation has become more challenging. This thesis expands the scope of Web QoE estimation methods to include interactivity. Two robust real-user monitoring metrics are proposed: the interactive Load Time (iLT) and the Total Completed interactive Load (TCiL). While the iLT metric measures the waiting time associated with the users' interactions, the TCiL metric represents the users' waiting time tolerance for contents to load. A subjective study confirms a logarithmic relationship between the iLT metric and the user-reported perceived quality. Furthermore, the computed TCiL metric confirms that the users are willing to wait for approximately two seconds before interrupting the content loading stage and taking the next action. A subsequent user study quantifies the minimum change in iLT measurement that users can discriminate. A programmable network framework is proposed and demonstrates that it is possible for the network to become aware of interactive web application QoE. The thesis further explores the influence of animated content on the visual perception of loading a web page. When the users perceive a page is visually complete on the screen, it is referred to as Above-The-Fold time (ATF time). An experimental design and methodology are presented to measure the perceived ATF time for websites with and without animated elements. A subjective experiment confirms that the pages with animated elements caused people to have a more diverse perception of ATF under different network conditions. It is illustrated that the over-estimated ATF time by the state-of-the-art metrics, negatively impact the QoE management of web applications. Motivated by this observation, a new metric, Plausibly Complete Time (PCT), is proposed to estimate the perceived ATF time for websites with different content characteristics, focusing on animated and non-animated content classes. The performance and the accuracy of the PCT metric is evaluated based on subjective data and a public dataset, showing a high correlation between PCT values and the subjective responses. It is shown that using PCT in QoE models improves the robustness of QoE estimation models in comparison to the objective ATF time. Finally, an exploration of the QoE estimation of interactive applications with immersive technologies beyond conventional web page navigation is undertaken. A Telepresence Robot (TPR) control system is employed to illustrate the different QoE dimensions of interactive applications. A subjective study is also designed to systematically assess remote navigation QoE. The experimental analysis demonstrates that the influence of network factors vary depending on the QoE aspect and the actual task at hand. The result shows that users can differentiate well between visual and navigation/control aspects of their experience.||Funding Details:||Science Foundation Ireland||Type of material:||Doctoral Thesis||Publisher:||University College Dublin. School of Computer Science||Qualification Name:||Ph.D.||Copyright (published version):||2020 the Author||Keywords:||QoE; Web; Quality; Metric||Language:||en||Status of Item:||Peer reviewed||This item is made available under a Creative Commons License:||https://creativecommons.org/licenses/by-nc-nd/3.0/ie/|
|Appears in Collections:||Computer Science Theses|
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