YouTube QoE Evaluation Tool for Android Wireless Terminals
📝 Original Info
- Title: YouTube QoE Evaluation Tool for Android Wireless Terminals
- ArXiv ID: 1405.4709
- Date: 2014-05-20
- Authors: Researchers from original ArXiv paper
📝 Abstract
In this paper, we present an Android application which is able to evaluate and analyze the perceived Quality of Experience (QoE) for YouTube service in wireless terminals. To achieve this goal, the application carries out measurements of objective Quality of Service (QoS) parameters, which are then mapped onto subjective QoE (in terms of Mean Opinion Score, MOS) by means of a utility function. Our application also informs the user about potential causes that lead to a low MOS as well as provides some hints to improve it. After each YouTube session, the users may optionally qualify the session through an online opinion survey. This information has been used in a pilot experience to correlate the theoretical QoE model with real user feedback. Results from such an experience have shown that the theoretical model (taken from the literature) provides slightly more pessimistic results compared to user feedback. Users seem to be more indulgent with wireless connections, increasing the MOS from the opinion survey in about 20% compared to the theoretical model, which was obtained from wired scenarios.💡 Deep Analysis
Deep Dive into YouTube QoE Evaluation Tool for Android Wireless Terminals.In this paper, we present an Android application which is able to evaluate and analyze the perceived Quality of Experience (QoE) for YouTube service in wireless terminals. To achieve this goal, the application carries out measurements of objective Quality of Service (QoS) parameters, which are then mapped onto subjective QoE (in terms of Mean Opinion Score, MOS) by means of a utility function. Our application also informs the user about potential causes that lead to a low MOS as well as provides some hints to improve it. After each YouTube session, the users may optionally qualify the session through an online opinion survey. This information has been used in a pilot experience to correlate the theoretical QoE model with real user feedback. Results from such an experience have shown that the theoretical model (taken from the literature) provides slightly more pessimistic results compared to user feedback. Users seem to be more indulgent with wireless connections, increasing the MOS fro