Video Transmission Over Varying Bandwidth Links

1. Video Transmission Over Varying Bandwidth Links MTP Final Stage Presentation By: Laxmikant Patil Under Guidance of Prof. Sridhar Iyer

2. Presentation Outline • Introduction & Motivation • Problem Definition • Related Work • Traffic Pattern based Adaptive Multimedia Multicast (TPAMM) Architecture • Solution Strategy • Simulation & Results • Conclusion • References

3. Introduction & Motivation Key Terms • Playout Rate: The rate at which video is shown at client • Delay Tolerant Applications: Clients can tolerate some delay before playout starts e.g. DEP offering live courses to remote students, Live concert streaming, MNCs training employees across cities • Startup Latency: Maximum duration of time client is ready to wait before playout starts

4. S 84 kbps R1 80 kbps 75 kbps C1 R2 = 20 70 kbps C2 C3 80 kbps = 30 = 40 Introduction & Motivation (Contd…) Need for Adaptive Mechanisms • Heterogeneity of receivers capabilities • Transmission capabilities • Displaying capabilities • Heterogeneity of receivers requirements • Delay tolerance values • Minimum acceptable quality

5. Stream at rate ai C S ai is bottleneck b/w, Time= L Encoding rate ai = ? C S ai is avg. b/w for TX Time= L + startup_latency ? ai = Base encoding rate Play S Time= L + Download duration Introduction & Motivation (Contd…) 3 ways to transfer data from source to client • Streaming solution • Partial download • Complete download C

6. Problem Definition • “Objective is to use to overcome the problem of variations in link bandwidth and provide consistent video quality to the client.” • We propose to use startup latency and prediction model based approach to overcome this

7. Example Given: • Startup latency = 5 min • Length of video L = 60 min • aavg = ?

8. Related work • [SAMM] Multilayering: Video is encoded as base layer and enhancement layers. • Client receive number of layers depending on their capabilities • Objective is to decide number of layers & encoding rates of each layer • [KRTCR] Transcoding : Changes the encoding rate of the video file to desired rate • Transcoding only at source • Transcoding at relay nodes • [AIMA] Buffer-based adaptation: uses occupancy of buffer on transmission path as a measure of congestion • [AVMI] Simulcast: Source maintains different quality stream and receiver switches across streams. Combination of single-rate multicast and multiple-unicast.

9. TPAMM Architecture (Traffic Pattern based Adaptive Multimedia Multicast)

10. Solution strategy • Single hop topology • Multi hop topology • Multicast tree topology • Prediction window & offset computation

11. C S Single hop topology • Find

12. C S Single hop topology (Contd…) • Need to find “Critical points” during transmission

13. Single hop topology (Contd…) Critical points : at t =100 sec (Accumulated Bw) < (Consumed Bw) No Critical points (Accumulated Bw) >= (Consumed Bw)

14. S R C Extra b/w but not useful deficit b/w at link R-C Compensate b/w R-C Effective deficit Multi hop topology (Source-Relay-Client Scenario)

15. Multihop scenario S R1 R2 Rn C

16. S 84 kbps R1 80 kbps 75 kbps C1 R2 = 20 70 kbps C2 C3 80 kbps = 30 = 40 Multicast Tree Topology

17. Prediction Window & Time-Offset Computation • Startup latency • Duration of video Encoding rate • All predictions values per interval Prediction window Last Prediction window • We modify algorithm to work for prediction window size, by computing time-offset. • Startup latency for next window = Current Startup latency + time-offset • Duration of video for next window = Current duration of video - time-offset

18. Prediction Window & Time-Offset Computation (Contd…) Prediction window Last Prediction window • Following values are known • Encoding rate for current feedback interval (e.g. 60 kbps) • Transmission rate for current feedback interval (e.g. 90 kbps) • Feedback interval duration (e.g. 10 sec) • Actual_playout_duration_Tx (A) is computed as (Encoding rate / Transmission rate ) * Feedback interval duration =15 sec • Expected_playout_duration_Tx (E) is computed as (current_playout_time) * Feedback interval duration = 10 sec (current_playout_time + current_startup_latency) • Time-offset = (Actual_playout_duration_Tx) – (Expected_playout_duration_Tx) • Time-offset for this example is 5 sec.

19. Simulation & Results • Effect of Delay Tolerance on Encoding Rate • As Delay Tolerance increases Encoding Rate also increases

20. Simulation & Results (Contd…) • Effect of Prediction Window size on Video Quality • Parameter: Standard deviation of encoding rate • As prediction window size increases, variations in video quality are reduced. • With small increase in prediction window size, there is significant drop in variation.

21. Simulation & Results (Contd…) • Effect of Prediction Window size on Video Quality • As prediction window size increases, variations in video quality are reduced.

22. Simulation & Results (Contd…) • Maximize Minimum Video Quality During Playout • Minimum Video Quality throughout playout is maximized in TPAMM scheme.

23. Conclusion • We have introduced a class of algorithms known as Traffic Pattern based Adaptive Multimedia Multicast (TPAMM) algorithms. • In TPAMM scheme abrupt link bandwidth variations are not reflected at client side, ensuring good user perceived video quality. • TPAMM scheme maximizes the minimum video quality during playout.

24. References • [SAMM] Brett Vickers, Albuquerque and Tatsuya Suda, Source-adaptive multi-layered multicast algorithm for real-time video distribution. IEEE/ACM Transactions on Networking, 8(6):720-733, 2000. • [AVMI] Jiangchuan Liu, Bo Li and Ya-Qin Zhang. Adaptive video multicast over the internet. IEEE Multimedia, 10(1):22-33,2003. • [KRTCR] Rajeev Kumar, JS Rao, AK Turuk, S. Chattopadhyay and GK Rao A protocol to support Qos for multimedia traffic over internet with transcoding www.ee.iastate.edu/~gmani/tiw-2002/internet-qos.pdf • [AIMA] X. Wang and H. Schulzrinne. Comparison of adaptive internet multimedia applications. In IEICE Trans. COMMUN. 1999.