QoE Doctor: Diagnosing Mobile App QoE with Automated UI Control and Cross-layer Analysis


Smartphones have become increasingly prevalent and important in our daily lives. To meet users' expectations about the Quality of Experience (QoE) of mobile applications (apps), it is essential to obtain a comprehensive understanding of app QoE and identify the critical factors that affect it. However, effectively and systematically studying the QoE of popular mobile apps such as Facebook and YouTube still remains a challenging task, largely due to a lack of a controlled and reproducible measurement methodology, and limited insight into the complex multi-layer dynamics of the system and network stacks. In this paper, we propose <i>QoE Doctor</i>, a tool that supports accurate, systematic, and repeatable measurements and analysis of mobile app QoE. QoE Doctor uses UI automation techniques to replay QoE-related user behavior, and measures the user-perceived latency directly from UI changes. To better understand and analyze QoE problems involving complex multi-layer interactions, QoE Doctor supports analysis across the application, transport, network, and cellular radio link layers to help identify the root causes. We implement QoE Doctor on Android, and systematically quantify various factors that impact app QoE, including the cellular radio link layer technology, carrier rate-limiting mechanisms, app design choices and user-side configuration options.

DOI: 10.1145/2663716.2663726

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@inproceedings{Chen2014QoEDD, title={QoE Doctor: Diagnosing Mobile App QoE with Automated UI Control and Cross-layer Analysis}, author={Qi Alfred Chen and Haokun Luo and Sanae Rosen and Zhuoqing Morley Mao and Karthik Iyer and Jie Hui and Kranthi Sontineni and Kevin Lau}, booktitle={Internet Measurement Conference}, year={2014} }