Soft ARQ for Streaming Layered Multimedia

• Authors: Matthew Podolsky;Steven McCanne
• Venue: Soft ARQ for Streaming Layered Multimedia
• Year: 1999

In contrast to multimedia applications that involve human-to-human communication, streaming media over the Internet enjoys relaxed delay constraints. Thus, streaming media servers are at liberty to retransmit missing packets to avoid unnecessary signal corruption. While state-of-the-art media servers employ such strategies, no work to date has proposed an optimal strategy for delay-constrained retransmissions of streaming media. In this paper, we propose a framework for streaming media retransmission based on layered media representations and explore the performance advantage of integrating layered signal structure into the retransmission strategy. In our approach, the source must choose between transmitting an older layer that expires sooner and a newer layer that expires later but is more important. To provide a quantitative performance comparison between these choices, we develop a Markov-chain analysis for transmitting layered data over a binary erasure channel with instantaneous feedback when network parameters such as erasure probability and transmission delay are fixed. The source has a maximum transmission rate constraint, due either to physical limitations of the channel or a limit imposed by rate-control. The key result of this analysis is that the optimal transmission policy is time-invariant and thus does not change as the layers approach their expiration times. Based on these results, we develop a transmission protocol which adapts to dynamic network conditions. Included in this protocol is a novel sender-based method for estimating if transmitted data will reach the receiver in time. Though this method accounts for the one-way transmission delay, it does so without requiring synchronized clocks at the source and receiver. We evaluate this protocol through simulation, and arrive at the following conclusions: there are significant performance benefits both from layering the media signal and adaptively estimating how much time is left to transmit the data, but the benefits of adapting transmission strategies to changing network conditions to are marginal.