On TV screens, PCs, tablets, and mobile phones, video streaming has become a constant companion in our daily lives. For every video, we expect high visual quality, free from distortions, that is adjusted to the device at hand. But how can streaming systems cope with the increasing network traffic, the subsequent network congestions, and the different characteristics of end-user terminals? This thesis covers approaches for distributed adaptation of scalable video resources in media delivery. Scalable video resources consist of several layers that enable various spatial resolutions, frame rates, or qualities of a content. By dropping some of these layers, the video can be adjusted to the available bandwidth or to a specific end-user terminal. The adaptation can be performed on the sender side, on the receiver side, and on one or more network nodes. Scalable media coding can also help to reduce bandwidth requirements in multicast scenarios (e.g., for IPTV). One popular realization of scalable media coding is the Scalable Video Coding (SVC) standard. This thesis consists of three main parts, addressing various challenges towards efficient SVC adaptation. The first part of this thesis focuses on the encoding of SVC. In order to enable efficient adaptation, the configuration of layers has to be carefully chosen at encoding time. Thus, the performances of various encoding configurations and encoder implementations are evaluated.
Furthermore, encoding guidelines for SVC are developed, which are aligned with recommendations of industry streaming solutions. The evaluation results of the developed SVC encoding guidelines suggest that quality scalability should be preferred over spatial scalability for adaptive streaming scenarios. Different resolutions for supporting device classes should rather be provided as separate SVC streams. The second part of this thesis deals with the fact that scalable media formats, such as SVC, are still not widely adopted neither on the sender side nor on the end-user terminal. In order to enable the deployment of SVC for network transmission and to improve the support for streaming to heterogeneous devices, the concept of SVC tunneling is introduced in this thesis. The video is transcoded to SVC at the sender side and then transcoded back to another video format at the receiver side at an advanced home-gateway. However, the transcoding between video formats has a negative impact on the video quality. The trade-off between quality loss and bandwidth efficiency of SVC tunneling is evaluated. SVC tunneling with quality layers enables bandwidth savings at moderate quality loss (approx. 2.5 dB) compared to streaming separate non-scalable representations of the same qualities. In the third part of this thesis, adaptation techniques for content-aware networks are investigated. In content-aware networks, some network nodes are capable to dynamically adapt video streams in reaction to varying network loads. With the increasing adoption of HTTP streaming, adaptation at the client side becomes a main factor for the viewing experience. The switch between two representations (e.g., different bitrates) of a video can disrupt that viewing experience. To reduce the effect of an abrupt quality change, the approach of a smooth transition between representations is developed and evaluated. A subjective user study indicates that this approach can indeed improve the overall viewing quality. Finally, the findings of the previous parts are integrated in an adaptive end-to-end SVC streaming system.
Evaluations of this streaming system show that the developed adaptation framework significantly improves the video quality under packet loss (by up to 6 dB) compared to non-adaptive streaming.