Next to You: Monitoring Quality of Experience in Cellular Networks From the End-Devices

• Published in: IEEE eTransactions on network and service management Vol. 13; no. 2; pp. 181 - 196
• Main Authors: Casas, Pedro, Seufert, Michael, Wamser, Florian, Gardlo, Bruno, Sackl, Andreas, Schatz, Raimund
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applications programs; Bandwidth; Crowdsourcing; End-device Measurements; Feedback; Field Trial; Mobile Apps; Mobile communication; Mobile communication systems; Monitoring; Networks; Provisioning; QoE; Quality of service; Smart phones; Smartphones; Subjective Lab Tests; YoMoApp; YouTube; mobile apps; crowdsourcing; end-device measurements; subjective lab tests; QoE; smartphones; YoMoApp; field trial
• ISSN: 1932-4537; 1932-4537
• DOI: 10.1109/TNSM.2016.2537645

A quarter of the world population will be using smartphones to access the Internet in the near future. In this context, understanding the quality of experience (QoE) of popular apps in such devices becomes paramount to cellular network operators, who need to offer high-quality levels to reduce the risks of customers churning for quality dissatisfaction. In this paper, we address the problem of QoE provisioning in smartphones from a double perspective, combining the results obtained from subjective laboratory tests with end-device passive measurements and QoE crowd-sourced feedback obtained in operational cellular networks. The study addresses the impact of both access bandwidth and latency on the QoE of five different services and mobile apps: YouTube, Facebook, Web browsing through Chrome, Google Maps, and WhatsApp. We evaluate the influence of both constant and dynamically changing network access conditions, tackling in particular the case of fluctuating downlink bandwidth, which is typical in cellular networks. As a main contribution, we show that the results obtained in the laboratory are highly applicable in the live scenario, as mappings track the QoE provided by users in real networks. We additionally provide hints and bandwidth thresholds for good QoE levels on such apps, as well as discussion on end-device passive measurements and analysis. The results presented in this paper provide a sound basis to better understand the QoE requirements of popular mobile apps, as well as for monitoring the underlying provisioning network. To the best of our knowledge, this is the first paper providing such a comprehensive analysis of QoE in mobile devices, combining network measurements with users QoE feedback in laboratory tests, and operational networks.