1. The Key Technologies for a Large-scale Real-time Interactive Video Distribution System 出處 :School of Electronics and Information Engineering 報告人 : 郭宇航 日期 :2013/12/23

2. Outline 1. INTRODUCTION 2. SPEED-PRIORITY REAL-TIME PEER-TO-PEER NETWORK 3. P2P NETWORKS SUPPORTING MULTI-USER REAL-TIME INTERACTION 4. THE EXPERIMENTAL RESULTS 5. CONCLUSIONS

3. INTRODUCTION 1/3 A real-time, interactive video distribution system on Internet for large-scale users faces three bottlenecks: 1.real-time performance 2.interactive performance 3. bandwidth pressure.

4. INTRODUCTION 2/3 This paper, based on the approach to establish a Real-time Peer-to-Peer network (RTP2P) 。 1.the minimum video data delay as the primary goal 2. establish a hybrid framework of P2P and centralized networks

5. INTRODUCTION 3/3 The key technologies include: 1.greedy scheduling algorithm 2.push-pull scheduling model 3.the hybrid network model.

6. SPEED-PRIORITY REAL-TIME PEER-TO-PEER NETWORK 1) The greedy pull scheduling algorithm. The continuous available video segments are most. The data delay is smallest.

7. The different result of the two algorithms

8. 2.Greedy push-pull scheduling algorithm The greedy scheduling algorithm, Node A will get the most video segments from one or two major partners. In this case, push and pull hybrid exchange can achieve greater efficiency.

9. The push method is used to get the most data from major partner while the pull method is used to get the debris segments from other partners.

10. P2P NETWORKS SUPPORTING MULTI-USER REAL-TIME INTERACTION In online education system, there are usually two or more speakers. P1.Every speaker-switch will cause the P2P networks reconstructed frequently. P2.The video delay between two speakers is too long.

11. The different data flow with different source node

12. In order to overcome the problems above, a hybrid model including C/S and P2P is generated, as shown in Figure 3.

13. P2P and C/S hybrid model

14. the process is described as follows: In the hybrid model, when the speaker A switches the speaking token to user C. a) User A leaves C/S network. b) User A restores the traffic in P2P network. c) User C suspends the traffic in P2P network. d) User C joins in C/S network and uploads its video data to server S.

15. THE EXPERIMENTAL RESULTS The system was developed with C / C + and Visual Studio 2003 under Windows platforms. The audio encoder is iLBC with 16kbps bitrate,16 kHz sampling. The video encoder is t264 with 140kbps bitrate, 176X144 resolution and 12frame per second. The default size of each node buffer is 1MBytes.

16. A. The impact of speaker-switch on video delay Select node A, B and C as the targets, and analysis their video delay during 30 minutes. Respectively, at the time t=10 minutes and t=20 minutes, a speaker-switch occurred.

17. Fig 4 The impact of speaker-switch on video delay

18. B. The value of nodes’ video delay In the experiment, we randomly sampled 50 nodes and recorded their video delay at the moment the total number N of nodes increased to 500, 1000 and 2000.

19. Fig 5. the 50 sampling nodes’ delay

20. C. Video continuity index When the number of nodes is respectively 200, 1000 and 2000, the local buffer size is set to 1MBytes and there are 1, 2 and 3 simultaneous speakers, the end nodes' video continuity index is figured out by Figure 6.

21. Fig 6 Bitrate on the impact of continuity index

22. When the number of nodes is 1000, the local buffer size are set to 0.5MBytes, 1MBytes and 5MBytes respectively and there are 1,2 and 3 simultaneous speakers, the end nodes' video continuity index is figured out by Figure 7.

23. Fig 7 The size of local buffer on the impact of continuity index

24. CONCLUSIONS 1/2 The test result proves, through an online education system with 2000 simultaneous users, that the end user’s video delay is within 10 seconds. Compared with the normal P2P video streaming system with the delay varies between 30 to 120 seconds.

25. CONCLUSIONS 2/2 RTP2P is a more real-time, lower bandwidth- costing network to distribute video stream, saving more than 90% of the bandwidth cost.