QoE of mobile video delivery

Cloud gaming is an emerging technology that combines cloud computing with computer games. Compared to traditional gaming, its core advantages include ease of development/deployment for developers, and lower technology costs for users given the potential to play on thin client devices. In this chapter, we firstly describe the approach, and then focus on the impact of latency, known as lag, on Quality of Experience, for so-called First Person Shooter games. We outline our approach to lag compensation whereby we equalize within reason the up and downlink delays in real-time for all players. We describe the testbed in detail, the open source Gaming Anywhere platform, the use of NTP to synchronise time, the network emulator and the role of the centralized log server. We then present results that firstly validate the mechanism and also use small scale and preliminary subjective tests to assess and prove its performance. We conclude the chapter by outlining ongoing and future work.

This chapter discusses prospects of QoE management for future networks and applications. After motivating QoE management, it first provides an introduction to the concept by discussing its origins, key terms and giving an overview of the most relevant existing theoretical frameworks. Then, recent research on promising technical approaches to QoE-driven management that operate across different layers of the networking stack is discussed. Finally, the chapter provides conclusions and an outlook on the future of QoE management with a focus on those key enablers (including cooperation, business models and key technologies) that are essential for ultimately turning QoE-aware network and application management into reality.

—This paper deals with a video content classification based on spatial and temporal information. The main goal of the paper is to find out whether the non-expert test subjects are able to correctly recognize the spatial and temporal information and how precise is the corresponding parameterization of video content based on these two attributes. Moreover, how well do the objective values provided by the tool deployed in this experiment correlate with the subjective ones. The subjective measurement has shown that the non-expert test subjects are able to correctly recognize the spatial and temporal information only for the extreme scenes in terms of the spatial and temporal information but have experienced some problems when it comes to a more granular classification. When it comes to the objective assessment, the SI and TI values provided by the tool used in this experiment correlate quite well with the subjective data obtained from the basic test for the spatial information.

People increasingly use their mobile phones and mobile data to access different media types, including video. Due to mobile phone limitations, but also due to the scarce bandwidth on mobile networks, video content is often adapted to fit with these requirements by reducing its quality. In this study we look into how the user preference for a certain multimedia content (e.g. video, audio, text and images or only text) and the usage of mobile data affects user preference for video quality. The results show a statistically significant difference in the video quality preference only for participants who reported that video is one of the preferred multimedia content types, and the ones who did not. We also discuss how these results could be used for multimedia streaming and in telecommunications marketing research to improve user experience and increase network operators and content provider revenues.