QoS framework for video streaming in home networks

In this thesis we present a new SNR scalable video coding scheme. An important advantage of the proposed scheme is that it requires just a standard video decoder for processing each layer. The quality of the delivered video depends on the allocation of bit rates to the base and enhancement layers. For a given total bit rate, the combination with a bigger base layer delivers higher quality. The absence of dependencies between frames in enhancement layers makes the system resilient to losses of arbitrary frames from an enhancement layer. Furthermore, that property can be used in a more controlled fashion. An important characteristic of any video streaming scheme is the ability to handle network bandwidth fluctuations. We made a streaming technique that observes the network conditions and based on the observations reconfigures the layer configuration in order to achieve the best possible quality. A change of the network conditions forces a change in the number of layers or the bit rate of these layers. Knowledge of the network conditions allows delivery of a video of higher quality by choosing an optimal layer configuration. When the network degrades, the amount of data transmitted per second is decreased by skipping frames from an enhancement layer on the sender side. The presented video coding scheme allows skipping any frame from an enhancement layer, thus enabling an efficient real-time control over transmission at the network level and fine-grained control over the decoding of video data. The methodology proposed is not MPEG-2 specific and can be applied to other coding standards. We made a terminal resource manager that enables trade-offs between quality and resource consumption due to the use of scalable video coding in combination with scalable video algorithms. The controller developed for the decoding process optimizes the perceived quality with respect to the CPU power available and the amount of input data. The controller does not depend on the type of scalability technique and can therefore be used with any scalable video. The controller uses the strategy that is created offline by means of a Markov Decision Process. During the evaluation it was found that the correctness of the controller behavior depends on the correctness of parameter settings for MDP, so user tests should be employed to find the optimal settings.