1. Video Quality Assessment and Comparative Evaluation of Peer-to-Peer Video Streaming Systems Aditya Mavlankar Pierpaolo Baccichet Bernd Girod Stanford University Stanford CA, USA Sachin Agarwal Jatinder Pal Singh Deutsche Telekom A.G., Laboratories Berlin, Germany

2. Mavlankar et al.: Comparative Evaluation of Peer-to-Peer Video Streaming Systems Jun. 25, 2008 2 Outline  Introduction to P2P live video streaming  Prior work on system performance assessment  Test-bed setup  Performance of tested systems

3. Mavlankar et al.: Comparative Evaluation of Peer-to-Peer Video Streaming Systems Jun. 25, 2008 3 P2P Live Video Streaming  Extension of P2P file-sharing  Low-cost and scalable delivery mechanism  Several deployed commercial implementations today  Increasing content / channels available

4. Mavlankar et al.: Comparative Evaluation of Peer-to-Peer Video Streaming Systems Jun. 25, 2008 4 Related Work on Performance Assessment  Networking related metrics, e.g. bandwidth usage, packet loss, continuity index, etc. – CoolStreaming [Zhang et al., 2005]: PlanetLab – PPLive [Hei et al., 2006]: packet sniffing and crawling – SopCast [Sentinelli et al., 2007]: “watching”, PlanetLab –...  No video PSNR results  No repeatable test conditions – Network conditions – Encoded video characteristics – Peer behavior  No fair head-to-head comparison of different systems

5. Mavlankar et al.: Comparative Evaluation of Peer-to-Peer Video Streaming Systems Jun. 25, 2008 5 Test-Bed Setup TU Munich, Germany (3) [Emulated HS Broadband] Stanford, CA (22) [Emulated HS Broadband] Test center Berlin, Germany Server 1, 2 Berlin, Germany (15) [Emulated HS Broadband] 128 X 2 192 X 2 576 X 2 1024 X 2 3072 X 3 576 X 16 1024 X 5 2048 X 1 576 X 9 1024 X 5 2048 X 1 52 Mbps ISP Datacenter Erfurt, Germany Internet Berlin, Germany (8) [Real HS Broadband] PLR, delay, jitter and bandwidth measured for representative real connections and emulated using NISTNet traffic shaper

6. Mavlankar et al.: Comparative Evaluation of Peer-to-Peer Video Streaming Systems Jun. 25, 2008 6 Encoded Video Stream  La Dolce Vita (Fellini, 1960)  24 fps, 352x240 pixels  H.264/AVC video codec, 400 kbit/sec CBR bitstream, 42 dB PSNR  I B B P B B P B B P... (I frame every second)  H.264 bitstream wrapped in Microsoft ASF container, if required by tested system  Last frame error concealment

7. Mavlankar et al.: Comparative Evaluation of Peer-to-Peer Video Streaming Systems Jun. 25, 2008 7 Peer Churn Model  30-minute simulation run  During each 6-minute time-slot – Peer on with probability 0.9 – Peer off with probability 0.1 – Peer can switch off for the rest of the run with probability 0.05  During last 5 minutes, peer off with probability 0.5

8. Mavlankar et al.: Comparative Evaluation of Peer-to-Peer Video Streaming Systems Jun. 25, 2008 8 Representative Results  Tested systems – System A: Tree-based, push approach – System B: Mesh-based, data-driven or pull approach  Emulation runs – Run 1: with traffic shaping (using NISTNet) – Run 2: without traffic shaping  Same realization of peer On-Off model for all runs

9. Mavlankar et al.: Comparative Evaluation of Peer-to-Peer Video Streaming Systems Jun. 25, 2008 9 Pre-Roll Delay about 30 sec enough for System A (tree-based) about 60 sec enough for System B (mesh-based)

10. Mavlankar et al.: Comparative Evaluation of Peer-to-Peer Video Streaming Systems Jun. 25, 2008 10 PSNR Drop (w/ traffic shaping) System A (tree-based) System B (mesh-based) 32

11. Mavlankar et al.: Comparative Evaluation of Peer-to-Peer Video Streaming Systems Jun. 25, 2008 11 PSNR Drop (w/o traffic shaping) System A (tree-based) System B (mesh-based) 32

12. Mavlankar et al.: Comparative Evaluation of Peer-to-Peer Video Streaming Systems Jun. 25, 2008 12 Statistics of Frame Freezes  Frames frozen (as percentage of total frames to be displayed)  Average no. of distinct frame-freeze events per client in 30 min. System A (tree-based)System B (mesh-based) Run 14.2%2.0% Run 23.0%0.2% System A (tree-based)System B (mesh-based) Run 16423 Run 240 2

13. Mavlankar et al.: Comparative Evaluation of Peer-to-Peer Video Streaming Systems Jun. 25, 2008 13 Statistics of Frame Freezes (cont.) Long frame freezes more likely with System B (mesh- based) System A (tree- based) employs content-aware prioritization

14. Mavlankar et al.: Comparative Evaluation of Peer-to-Peer Video Streaming Systems Jun. 25, 2008 14 No. of Peers Failing to Decode a Frame System A (tree-based), Run 1 System B (mesh-based), Run 1

15. Mavlankar et al.: Comparative Evaluation of Peer-to-Peer Video Streaming Systems Jun. 25, 2008 15  Redundancy (bytes received in excess of required video stream bytes) – System A (tree-based): 6% in both runs – System B (mesh-based): 35% and 20% in Runs 1 (w/ traffic shaping) and 2 (w/o traffic shaping) respectively  For both Systems, peer receives on average less than 10% of its data directly from the server; slightly more for Run 2 of System B  System A (tree-based): Sustained downloads from lower number of parent peers Redundancy, Server Load and Parent-Peer Analysis

16. Mavlankar et al.: Comparative Evaluation of Peer-to-Peer Video Streaming Systems Jun. 25, 2008 16 Summary  Proposed methodology allows measuring video PSNR, buffering time, frame-freeze statistics, peers failing to decode a frame, etc. beyond network usage, packet loss, etc.  Test conditions chosen by analyzing real-world conditions and experiments are repeatable  Tested three commercial-grade P2P video streaming systems  Room for improvement in current systems: – Long buffering time (10s of seconds) – Display freezes for more than 100 frames  Tested tree-based system outperforms mesh-based system: – Redundancy – Buffering time

17. Thank you! http://www.stanford.edu/~maditya/publication.html Related: [Agarwal, et al., TRIDENTCOM 2008]