Rate-Distortion Optimized Distributed Packet Scheduling of Multiple Video Streams over Shared Communication Resources

We consider the problem of distributed packet selection and scheduling for multiple video streams sharing a communication channel. An optimization framework is proposed, that enables the multiple senders to coordinate their packet transmission schedules, such that the average quality over all video clients is maximized. The framework relies on rate-distortion information that is used to characterize a video packet. This information consists of two quantities: the size of the packet in bits, and its importance for the reconstruction quality of the corresponding stream. A distributed streaming strategy then allows for trading off rate and distortion, not only within a single video stream, but also across different streams. Each of the senders allocates to its own video packets a share of the bandwidth available on the communication channel, that is proportional to the relative importance of these packets. We evaluate the performance of the distributed packet scheduling algorithm for two canonical problems in streaming media, namely adaptation to available bandwidth and adaptation to packet loss. Simulation results demonstrate that, for the difficult case of scheduling non-scalably encoded video streams, our framework is shown to be very efficient in terms of video quality, both over all streams jointly and also over the individual videos. Compared to a conventional streaming system that does not consider the relative importance of the video packets, the gains in performance range up to 6 dB for the scenario of bandwidth adaptation and even up to 10 dB for the scenario of random packet loss adaptation

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

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

Utility-based Packet Scheduling in P2P Mesh-based Multicast

We consider streaming video content over an overlay network of peer nodes. We propose a novel streaming strategy that is built on utility-based packet scheduling and proportional resource sharing in order to fight against free- riders. Each of the peers employs a mesh-pull mechanism to organize the download of media packets from its neighbours. For efficient resource utilization, data units are requested from neighbours based on their utility. The packet utility is driven by both its importance for the video reconstruction quality at the receiving peer and its popularity within the peer neighbourhood. In order to discourage free-riding in the system, requesting peers then share the upload bandwidth of a sending peer in proportion to their transmission rate to that peer . Our simulation results show that the proposed protocols increase the performance of a mesh-pull P2P streaming system. Significant improvements are registered relative to existing solutions in terms of average quality and average decoding rate

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

Cooperative media streaming using adaptive network compression

Media content distribution constitutes a growing share of the services on the Internet. Two distinct distribution approaches used today are Layered Coding (LC) and Multiple Description Coding (MDC). Current wireless connection technologies, e.g. Wimax, have properties which make them unsuitable for media distribution using traditional approaches. In particular, the asymmetric relationship between the uplink and the downlink bandwidth makes the cooperative distribution difficult. A promising concept, termed MDC with Conditional Compression (MDC-CC), has been proposed [11], which essentially acts as an adaptive hybrid between LC and MDC. In order to facilitate the use of MDC-CC, a new overlay network approach is proposed, using tree of meshes. A control system for managing description distribution and compression in a small mesh is implemented in the discrete event simulator NS-2. The two traditional approaches, MDC and LC, are used as references for the performance evaluation of the proposed scheme. The system is simulated in a heterogeneous network environment, where packet errors are introduced. Moreover, a test is performed at different network loads. Performance gain is shown over both LC and MDC