This paper presents a framework for efficiently streaming scalable video from multiple servers over heterogeneous network paths. We propose to use rateless codes, or Fountain codes, such that each server acts as an independent source, without the need to coordinate its sending strategy with other servers. In this case, the problem of maximizing the received video quality and minimizing the bandwidth usage, is simply reduced to a rate allocation problem. We provide an optimal solution for an ideal scenario where the loss probability on each server-client path is exactly known. We then present a heuristic-based algorithm, which implements an unequal error protection scheme for the more realistic case of imperfect knowledge of the loss probabilities. Simulation results finally demonstrate the efficiency of the proposed algorithm, in distributed streaming scenarios over lossy channels

This paper addresses the problem of optimizing the playback delay experienced by a population of heterogeneous clients, in video streaming applications. We consider a typical broadcast scenario, where clients subscribe to different portions of a scalable video stream, depending on their capabilities. Clients share a common channel, whose limited rate directly drives the playback delays imposed to the different groups of receivers. We derive an optimization problem, that targets a fair distribution of the playback delays among heterogeneous clients. A server-based scheduling strategy is then proposed, that takes into account the properties of the targeted clients, the channel status, and the structure of the media encoding. It is shown to offer significantly reduced playback delays per client population, as compared to traditional scheduling strategies. In the same time, PSNR performance is not affected, which altogether leads to an overall improvement of the quality of service

We consider the problem of distributing high-quality video signals over IP multicast in large local area networks (LANs), under realtime delay constraints, and with software-only processing. In a large LAN (such as the network of a university campus, or the network of a large company), the source of channel heterogeneity that the video communications system must cope with is not that of different bandwidth constraints available to each receiver, but it is essentially variations in the available CPU power that each receiver has in order to decode the incoming signal. We propose a new architecture for a video multicast system, present the design of the different components of this system, and show results obtained in a real implementation. Our feeds consist of video encoded at about 3 Mbits/sec and 16 frames/sec, capable of tolerating the loss of about 300 Kbits/sec worth of data. Decoding is performed on Linux PCs, and the quality of our reconstructed signals degrades gracefully with the speed of the CPU on which the receiver runs.