Abstract

The volume of multimedia data, including video, served through Peer-to-Peer (P2P) networks is growing rapidly. Unfortunately, high bandwidth transfer rates are rarely available to P2P clients on a consistent basis. In addition, the rates are more variable and less predictable than in traditional client–server environments, making it difficult to use P2P networks to stream video for on-line viewing rather than for delayed playback.

In this paper, we develop and evaluate on-line algorithms that coordinate the pre-fetching of scalably-coded variable bit-rate video. These algorithms are ideal for P2P environments in that they require no knowledge of the future variability or availability of bandwidth, yet produce a playback whose average rate and variability are comparable to the best off-line pre-fetching algorithms that have total future knowledge. To show this, we develop an off-line algorithm that provably optimizes quality and variability metrics. Using simulations based on actual P2P traces, we compare our on-line algorithms to the optimal off-line algorithm and find that our novel on-line algorithms exhibit near-optimal performance and significantly outperform more traditional pre-fetching methods.

Keywords: P2P; Video; Streaming; Quality; Scheduling

Article Outline

1. Introduction

1.1. Prior work

2. Scalably coded videos in peer-to-peer networks

2.1. Scalable coding

3. Problem formulation

3.1. The model

3.1.1. Constructing the epoch view

3.1.2. Coordinating download of a single chunk

3.2. Performance measures

4. An optimal off-line algorithm

5. On-line allocation algorithms

5.1. Naive allocators

5.2. Constrained allocators

6. Results

6.1. Experimental setup

6.2. Simulated bandwidth

6.2.1. Analysis of simulations

6.3. Bandwidth traces

6.3.1. T1 connection

6.3.2. DSL connection

6.3.3. Analysis of trace results

7. Issues

8. Conclusion

References

Vitae