Distributed rate allocation for multi-flow video delivery

We consider rate-distortion (RD) optimized multi-flow video delivery in unstructured overlay networks. We show that this problem can be studied as a distributed rate allocation. To solve the problem over the participating peers in the overlay, we apply classical decomposition techniques such that the network-wide utility of video distortion is minimized. Media packets are assumed to be piggy-backed with RD preambles that contain information regarding their impact on decoder video distortion and their size. This allows for converting the calculated optimal rate allocation at every node into simple forwarding or dropping actions. Furthermore, the proposed distributed media streaming framework employs a network inference algorithm for minimizing the flow of duplicate packets over the network and utilizing thus more efficiently the available resources. Our simulation results indicate that significant quality benefits can be achieved when the precise RD characteristics of a media presentation are taken into account

Distributed Sender-Driven Video Streaming

A system for sender-driven video streaming from multiple servers to a single receiver is considered in this paper. The receiver monitors incoming packets on each network path and returns, to the senders, estimates of the available bandwidth on all the network paths. The senders in turn employ this information to compute transmission schedules for packets belonging to the video stream sent to the receiver. An optimization framework is proposed that enables the senders to compute their transmission schedules in a distributed way, and yet to dynamically coordinate them over time such that the resulting video quality at the receiver is maximized. Experimental results demonstrate that the proposed streaming framework provides superior performance over distortion-agnostic transmission schemes that perform proportional packet scheduling based only on the available network bandwidths

Low-Complexity Adaptive Streaming via Optimized A Priori Media Pruning

Abstract — Source pruning is performed whenever the data rate of the compressed source exceeds the available communication or storage resources. In this paper, we propose a framework for rate-distortion optimized pruning of a video source. The framework selects which packets, if any, from the compressed representation of the source should be discarded so that the data rate of the pruned source is adjusted accordingly, while the resulting reconstruction distortion is minimized. The framework relies on a rate-distortion preamble that is created at compression time for the video source and that comprises the video packets ’ sizes, interdependencies and distortion importances. As one application of the pruning framework, we design a low-complexity rate-distortion optimized ARQ scheme for video streaming. In the experiments, we examine the performance of the pruning framework depending on the employed distortion model that describes the effect of packet interdependencies on the reconstruction quality. In addition, our experimental results show that the enhanced ARQ technique provides significant performance gains over a conventional system for video streaming that does not take into account the different importance of the individual video packets. These gains are achieved without an increase in packet scheduling complexity, which makes the proposed technique suitable for online R-D optimized streaming. I

Fair Quality of Experience (QoE) Measurements Related with Networking Technologies

[Invited Talk] Eighth International Conference on Wired/Wireless Internet Communications (June 1-3, Luleå, Sweden)Proceeding of: 8th International Conference, WWIC 2010, Lulea, Sweden, June 1-3, 2010This paper addresses the topic of Fair QoE measurements in networking. The research of new solutions in networking is oriented to improve the user experience. Any application or service can be im- proved and the deployment of new solutions is mandatory to get the user satisfaction. However, different solutions exist; thus, it is necessary to select the most suitable ones. Nevertheless, this selection is difficult to make since the QoE is subjective and the comparison among different technologies is not trivial. The aim of this paper is to give an overview on how to perform fair QoE measurements to facilitate the study and re- search of new networking solutions and paradigms. However, previously to address this problem, an overview about how networking affects to the QoE is provided.This work has been funded by the CONTENT NoE from the European Commission (FP6- 2005-IST-41) and by the Ministry of Science and Innovation under the CON- PARTE project (MEC, TEC2007-67966-C03-03/TCM) and T2C2 project grant (TIN2008-06739-C04-01).Publicad