A Source Adaptive Multi-layered Multicast Algorithm for Internet

Layered transmission of data is often recommended as a solution to the problem of varying bandwidth constraints in multicast applications. In the case of video multicast, this technique encodes multiple interdependent layers of video at arbitrary target rates in order to address heterogeneous bandwidth constraints between the source and multiple receivers. However, multi-layered encoding alone is not sufficient to provide high video quality and high bandwidth utilization, because bandwidth constraints change over time. Adaptive techniques capable of adjusting the rates of video layers are required to maximize video quality and network utilization. In this paper we define a class of algorithms known as Source-Adaptive Multilayered Multicast (SAMM) algorithms. In SAMM algorithms, the source uses congestion feedback to adjust the number of generated layers and the bit rate of each layer. Furthermore, we introduce an end-to-end SAMM algorithm, in which only end systems monitor available bandwidth and report the amount of available bandwidth to the source. Using simulations that incorporate actual multi-layered video codecs, we demonstrate that the proposed SAMM algorithm exhibits better scalability and responsiveness to congestion than algorithms that are not source-adaptive.