Selim Ickin

Factors influencing quality of experience of commonly used mobile applications

Increasingly, we use mobile applications and services in our daily life activities, to support our needs for information, communication or leisure. However, user acceptance of a mobile application depends on at least two conditions: the applications perceived experience, and the appropriateness of the application to the users context and needs. However, we have a weak understanding of a mobile users quality of experience (QoE) and the factors influencing it. This article presents a 4-week-long 29-Androidphone- user study, where we collected both QoE and the underlying networks quality of service measurements through a combination of user, application, and network data on the users phones. We aimed to derive and improve the understanding of users QoE for a set of widely used mobile applications in users natural environments and different daily contexts. We present data acquired in the study and discuss implications for mobile applications design.

The effects of Packet Delay Variation on the perceptual quality of video

The satisfaction of end-users is important when evaluating services and products. Visualizing the network behavior in mobile streaming as well as modeling the correlation between Quality of Service (QoS) and Quality of Experience (QoE) is expected to improve user satisfaction of services on the Internet. Given that network and human factors are the elements that affect the final output of the measurements, it is important to take the Packet Delay Variation (PDV) into consideration. In this paper we observe the PDV during a series of real-life experiments on a 3rd Generation (3G) network while streaming videos. User Rating (UR) values from user input are recorded accordingly. With this aim, we implemented a QoE assessment tool that measures network metrics in kernel space, while simultaneously logging user ratings with regards to the perception of an ongoing realtime video on an Android phone. The primary goal is to identify a clear trend in the QoE modeling, so that we can assess the satisfaction of a user by deriving the QoE from measurable QoS metrics. We find that PDV degrades user perception. Observations show that, during the experiments, sudden breaks and restarts in the packet flow exist. Even though the use of Exponentially Weighted Moving Average (EWMA) assists in finding a model that shows the relationship between PDV and UR, on-off flushing is a major threat affecting this relationship. The results show that correlations with different quality can be reached with various modifications of the proposed matching model.

Studying the experience of mobile applications used in different contexts of daily life

Mobile applications and services increasingly assist us in our daily life situations, fulfilling our needs for information, communication, entertainment or leisure. However, user acceptance of a mobile application depends on at least two conditions; the applications perceived Quality of Experience (QoE) and the appropriateness of the application to the users situation and context. Yet, there is generally a weak understanding of a mobile users QoE and the factors influencing it. The mobile users experience is related to the Quality of Service (QoS) provided by the underlying service and network infrastructures, which provides a starting point for our work. We present work-in-progress results from an ongoing study of Android phone users. In this study, we aim to derive and improve understanding of their QoE in different situations and daily life environments. In particular, we evaluate the users qualitative QoE for a set of widely used mobile applications in the users natural environments and different contexts, and we analyze this experience and its relation to the underlying quantitative QoS. In our approach we collect both QoE and QoS measures through a combination of user, application and network input from mobile phones. We present initial data acquired in the study and derived from that, a set of preliminary implications for mobile applications design.

VLQoE: Video QoE instrumentation on the smartphone

The usage of network-demanding applications is growing rapidly such as video streaming on mobile terminals. However, network and/or service providers might not guarantee the perceived quality for video streaming that demands high packet transmission rate. In order to satisfy the user expectations and to minimize user churn, it is important for network operators to infer the end-user perceived quality in video streaming. Today, the most reliable method to obtain end-user perceived quality is through subjective tests, and the preferred location is the user interface as it is the closest point of application to the end-user. The end-user perceived quality on video streaming is highly influenced by occasional freezes; technically the extraordinary time gaps between two consecutive pictures that are displayed to the user, i.e., high inter-picture time. In this paper, we present a QoE instrumentation for video streaming, VLQoE. We added functionality to the VLC player to record a set of metrics from the user interface, application-level, network-level, and from the available sensors of the device. To the best of our knowledge, VLQoE is the first tool of its kind that can be used in user experiments for video streaming. By using the tool, we present a two state model based on the inter-picture time, for the HTTP- and RTSP-based video streaming via 3.5G. Next, we studied the influence of inter-picture time on the user perceived quality through out a user study. We investigated the minimum user perceived inter-picture time, and the user response time.

QoE-based energy reduction by controlling the 3g cellular data traffic on the smartphone

One of the most influencing factors on the overall end-user perceived quality from applications and services, i.e., QoE, running on the smartphones is their limited battery life. Particular cloud-based applications/services on the smartphone with a constrained battery life might consume high energy even when the smartphone is in screen-OFF state. The cellular radio module of the smartphone is one of the most power-consuming components, which depends on the running applications information polling characteristics that eventually cause the radio module to toggle occasionally between the cellular data energy states even during a sleep state. In this paper, we investigate the energy consumption of a set of applications that tend to retain up-to-date information via aggressive polling patterns. We show that limiting the network traffic and increasing the resource utilization efficiency amongst the applications and services can highly reduce the total energy consumption. We control the network activity of a smartphone with different cellular data-enabled and data-disabled durations at the screen-OFF state. First, we run controlled-lab energy measurements to have a ground truth on the power consumption patterns of a set of cloud-based popular applications/services; and next we conduct a subjective study with our proposed solution (ExpCO2), to understand first the user behaviour on the smartphone and then present how the reduced polling intervals of applications and notifications influence the end-user perceived quality. We indicate that ExpCO2 has a potential to save energy.

Studying the challenges in assessing the perceived quality of mobile-phone based video

Evaluating video Quality of Experience (QoE) on a mobile phone has not yet been studied much. It is common that the data collected through user studies in mobile platform involves high fluctuation of user ratings without obvious reasons related to variation in network level. User disparity, users various intermediate or previous experiences, video bitrate, and the objective measure of criticality are a few of the reasons that need to be identified with a well-designed user experiment. We present an experiment procedure to understand better the perceived quality of video in mobile platform. First, we investigate the reliability of the data, and identify unreliable users. Then, we investigate the psychological influence factors of previous experiences on the recent perceived quality known as the memory effect, and the influence of the bitrate on the time it takes for users to react and evaluate the video quality, i.e., user response time.

Evaluation of challenges in human subject studies "in-the-wild" using subjects' personal smartphones

The experimental setting of Human Mobile Computer Interaction (HCI) studies is moving from the controlled laboratory to the users daily-life environments, while employing the users own smartphones. These studies are challenging for both new and expert researchers in human subject studies in the HCI field. Within the last three years, we conducted three different smartphone-based user studies. From these studies, we have derived key challenges that we successfully overcame during their execution. In this paper, we present the outcomes and explain the adopted solutions for the challenges identified in the design, development and execution, and data analysis phases during the user studies. Our goal is to give newcomers and junior researchers a practical view on our conducted studies, and help practitioners to reflect on their own studies and possibly apply the proposed solutions.

PERIMETER: A user-centric mobility framework

This demo shows a prototype of a user-centric mobility framework that provides handover for macro-mobility on handheld devices. The framework is designed for mobile-controlled handover and does not require modification of the Internet infrastructure. The end-users are so able to control the roaming process governed by user considerations in addition to business objectives. To achieve seamless mobility UDP tunneling is used as a basis for the handover process. Additionally, measurements are performed on the tunnels to acquire Quality of Service (QoS) metrics and hence serve for roaming decision making processes.

Energy saving approaches for video streaming on smartphone based on QoE modeling

In this paper, we study the influence of video stalling on QoE. We provide QoE models that are obtained in realistic scenarios on the smartphone, and provide energy-saving approaches for smartphone by leveraging the proposed QoE models in relation to energy. Results show that approximately 5J is saved in a 3 minutes video clip with an acceptable Mean Opinion Score (MOS) level when the video frames are skipped. If the video frames are not skipped, then it is suggested to avoid freezes during a video stream as the freezes highly increase the energy waste on the smartphones.

Catching the download train: Energy-efficient file downloading on smartphones

The most energy-consuming applications in battery life-constrained smartphones are the ones that comprise data transmission, especially via the 3G interface. Scheduling download activities on smartphones is especially necessary, if there are multiple asynchronous downloads scattered over a long duration. The latter scenario highly increases the energy consumption of smartphones. In this paper, we investigate energy consumption with the focus on file downloading while scheduling multiple file downloads in two scenarios: serialized and parallel. We repeat the experiments on a single smartphone via its 3G and also via WiFi tethering via another smartphone. We assess the performance of the two scenarios via measurement of power consumption and corresponding download duration in a realistic environment.