Quality of Experience on Smartphones : Network, Application, and Energy Perspectives

Abstract

Smartphones have become crucial enablers for users to exploit online services such as learning, leisure, communicating, and socializing. The user-perceived quality of applications and services is an important factor to consider, in order to achieve lean resource management, to prevent user churn and revenue depletion of service or network providers. This is often studied within the scope of Quality of Experience (QoE), which has attracted researchers both in academia and industry. The objective of this thesis is to study the most important factors influencing QoE on smartphones and synthesize solutions for intervention. The temporal impairments during a real-time energy-hungry video streaming are studied. The aim is to quantify the influence of temporal impairments on the user-perceived video QoE at the network and application level together with energy measurements, and also to propose solutions to reduce smartphone energy consumption without degrading the user’s QoE on the smartphone for both user-interactive, e.g., video, and non-interactive cases. QoE measurements on smartphones are performed throughout in-the-wild user studies. A set of quantitative Quality of Experience (QoE) assessment tools are implemented and deployed for automatic data logging at the network- and application-level. Online momentary survey, Experience Sampling Method (ESM) software, and Day Reconstruction Method (DRM) along weekly face-to-face user interviews are employed. The subjective QoE is obtained through qualitative feedback including Mean Opinion Score (MOS) as well as in-situ indications of poor experiences by users. Additionally, energy measurements on smartphones are conducted in controlled-lab environment with the Monsoon device. The QoE of smartphone applications and services perceived by users depends on many factors including anomalies in the network, application, and also the energy consumption. At the network-level, high packet delay variation causes long video freezes that eventually impact negatively the end-user perceived quality. The freezes can be quantified as large time gaps in-between the displayed pictures during a video stream at the application-level. We show that the inter-picture time in cellular-based video stream can be represented via two-state exponential ON/OFF models. We show models representing the non-linear relationship between the QoE and the mean inter-picture time. It is shown that energy measurements help to reveal the temporal impairments in video stream enabling energy consumption as a QoE indicator. Next, energy waste and saving during temporal impairments are identified. Additionally, other video streaming use cases, e.g., “download first and watch later”, are studied and appropriate energy-saving download scheduling mechanisms are recommended. The possibility for decreasing energy consumption when the smartphone screen is OFF, while maintaining QoE, is revealed. We first show exponential models to represent user’s interaction with smartphone, then propose a NyxEnergySaver software, to control the cellular network interface in a personalized manner to save smartphone energy. According to our findings, more than 30% smartphone energy can be saved without impacting the user-perceived QoE