Understanding user experience of mobile video: Framework, measurement, and optimization

Since users have become the focus of product/service design in last decade, the term User eXperience (UX) has been frequently used in the field of Human-Computer-Interaction (HCI). Research on UX facilitates a better understanding of the various aspects of the user’s interaction with the product or service. Mobile video, as a new and promising service and research field, has attracted great attention. Due to the significance of UX in the success of mobile video (Jordan, 2002), many researchers have centered on this area, examining users’ expectations, motivations, requirements, and usage context. As a result, many influencing factors have been explored (Buchinger, Kriglstein, Brandt & Hlavacs, 2011; Buchinger, Kriglstein & Hlavacs, 2009). However, a general framework for specific mobile video service is lacking for structuring such a great number of factors. To measure user experience of multimedia services such as mobile video, quality of experience (QoE) has recently become a prominent concept. In contrast to the traditionally used concept quality of service (QoS), QoE not only involves objectively measuring the delivered service but also takes into account user’s needs and desires when using the service, emphasizing the user’s overall acceptability on the service. Many QoE metrics are able to estimate the user perceived quality or acceptability of mobile video, but may be not enough accurate for the overall UX prediction due to the complexity of UX. Only a few frameworks of QoE have addressed more aspects of UX for mobile multimedia applications but need be transformed into practical measures. The challenge of optimizing UX remains adaptations to the resource constrains (e.g., network conditions, mobile device capabilities, and heterogeneous usage contexts) as well as meeting complicated user requirements (e.g., usage purposes and personal preferences). In this chapter, we investigate the existing important UX frameworks, compare their similarities and discuss some important features that fit in the mobile video service. Based on the previous research, we propose a simple UX framework for mobile video application by mapping a variety of influencing factors of UX upon a typical mobile video delivery system. Each component and its factors are explored with comprehensive literature reviews. The proposed framework may benefit in user-centred design of mobile video through taking a complete consideration of UX influences and in improvement of mobile videoservice quality by adjusting the values of certain factors to produce a positive user experience. It may also facilitate relative research in the way of locating important issues to study, clarifying research scopes, and setting up proper study procedures. We then review a great deal of research on UX measurement, including QoE metrics and QoE frameworks of mobile multimedia. Finally, we discuss how to achieve an optimal quality of user experience by focusing on the issues of various aspects of UX of mobile video. In the conclusion, we suggest some open issues for future study

Device-oriented energy-aware utility-based priority scheduler for video streaming over LTE system

Nowadays people tend to spend most of their time in front of a screen, and expect to be able to connect to the Internet anytime and anywhere and from any type of mobile device. Therefore, fast surfing speed on Internet, high resolution display screen, advanced multi-core processor and lasting battery support are becoming the significant standards in the nowadays mobile devices. In this context the network operators must be able to differentiate between their multiscreen offerings in order to ensure uninterrupted, continuous, and smooth video streaming with minimal delay, jitter, and packet loss. This paper proposes a novel Device-Oriented Energy-Aware Utility-based Priority scheduling (DE-UPS) algorithm which makes use of device differentiation in order to ensure seamless multimedia services over LTE networks. The priority decision is based on the device classification, energy consumption of the mobile device and the multimedia stream tolerance to packet loss ratio

QoE for Mobile Streaming

No abstract

Performance of an adaptive multimedia mechanism in a wireless multi-user environment

With the increasing popularity of accessing multimedia services over different wireless networks, researchers have been trying to develop different adaptive multimedia mechanisms in order to mitigate the impact of fluctuating radio resources. This paper considers the case when multiple users stream video over the same IEEE 802.11b WLAN using a newly proposed Signal Strength-based Adaptive Multimedia Delivery Mechanism (SAMMy). SAMMy makes use of the IEEE 802.11k standard and uses estimated signal strength, location, and packet loss as part of its adaptive mechanism in order to increase user perceived quality for multimedia streaming applications in wireless networks. SAMMy is evaluated by modeling and simulations and compared with another adaptive multimedia delivery mechanism TFRC, in terms of aggregate throughput and fairness. The results show that the proposed signal strengthbased adaptive multimedia delivery scheme outperforms the other scheme in terms of both throughput and fairness when performing video streaming in WLAN