1. Dr. Charles Krasic*, Anirban Sinha* and Lowell Kirsh** * University of British Columbia, Vancouver, Canada. ** Amazon Inc, Seattle, USA. 1

2. Motivation Multimedia capable networked devices are heterogeneous – from powerful desktops to resource constricted mobile devices. In a single device, in addition to overall capabilities, there can be competition for resource sharing between various applications. 2

3. Motivation (Contd...) Streaming media must be able to scale to the diversity of available hardware as well as time varying nature of available resources. Priority-Progress Streaming is a method for bandwidth-adaptive streaming. This paper: apply the same basic Priority-Progress concepts toward making “CPU-adaptive” applications. 3

4. CPU Burstiness of Video 4

5. The Problem CPU requirements for a single video often vary greatly over the time, in correlation with bitrate. Device diversity and resource dynamics make over provisioning impractical. We need a mechanism for graceful adaptation hopefully maximizing quality (hence CPU) utilization – its tough! 5

6. Adaptation Performance of Popular Video Applications We take VLC and MPlayer and instrument them to measure their temporal fidelity – measured using two matrices: Jitter – time delta between successive frame displays, captures visible playback stoppage. FPS - idea of overall smoothness of video. 6

7. Adaptation Performance of Popular Video Applications(Contd...) We play N simultaneous videos (all same video), in each of VLC and MPlayer for N = 2 to 6 We select two values of N; N sat that just saturates the CPU and N 2 x sat which is twice the value of N sat. Both VLC and MPlayer have some capability to adapt to higher CPU loads; viz. through dropping of frames. We expect adaptation to occur in N 2xsat case. For both players, we found N sat = 3 and thus N 2 x sat = 6 7

8. VLC & MPlayer in underload (a) VLC in underload for one single video Total 3 videos (typical case for all videos) (b) MPlayer in underload for one single video Total 3 videos (typical case for all videos) 8

9. VLC and MPlayer in Underload – Summary In under load, all players perform well; MPlayer requires 14% less CPU than VLC. Jitter in underload is uninteresting because with FPS = 24 and no frame dropping, basic jitter is approximately 41.7 ms in all cases. 9

10. VLC & MPlayer in Overload – FPS and Jitter for a single video (a) VLC in overload (one player out of 6) (b) MPlayer in overoad (one player out of 6) 10

11. VLC & MPlayer in Overload – Fairness across videos (a) VLC in overload – All videos(b) MPlayer in overoad – All videos 11

12. VLC & MPlayer in Overload – Summary MPlayer exhibits bimodal fairness with some videos experiencing almost full frame rate and others experiencing very low frame rate. Overall MPlayer shows greater consistency towards frame dropping. Fairness for VLC across all videos is very poor. We suspect the differences between MPlayer and VLC as partly due to their architectural differences – VLC is multithreaded whereas MPlayer is event driven. 12

13. Priority-Progress Decoding In this paper, we design, implement and evaluate Priority-Progress Decoding derives from our previous work on bandwidth-adaptive streaming Priority-Progress Streaming Sclalable Video codec, our variant of MPEG-4, called SPEG4 Priority Mapper, translates declarative policies and raw video into appropriately prioritized ADUs Priority-Progress, adaptive streaming algorithm/protocol 13

14. Declarative Adaptation Policy Specification specify preferences instead of actions Specifications consists of a set of utility functions, one per quality dimension Mapper transforms policy specs into an executable adaptation strategy A streaming mechanism executes the adaptation 1 0 Quality Loss Utility As good as Perfect Useless 14

15. Priority-Progress Adaptation Take prioritized layered application data (SPEG + mapper), and apply adapation window in original PPS, window did not slide, it does in PPD before resource constraint (Network, or CPU) take video with window boundaries (time based) re-order from original (time) order to priority order on completion of each step, re-order data into time order if time runs out, drop remaining low-priority data Ongoing work: “window scaling”, spatial quality 15

16. QStream Performance with equal Utility Specification (a) QStream in underload (4 videos)(b) QStream in overload (8 videos) 16

17. QStream Performance with Preferential Utility Function Specified for Selected Video (a) QStream in underload (4 videos)(b) QStream in overload (8 videos, 1 boosted in importance) 17

18. QStream Jitter in Overload and Underload. (a) QStream in underload (4 videos)(b) QStream in overload (8 videos) 18

19. QStream Results – Summary QStream adapts gracefully and uniformly to increased CPU load across all videos. Jitter even in overload is reasonable and uniform and proportional to the number of frames dropped. QStream allows relative importance of streams to be specified; allowing control over quality—regardless of complex resource implications. 19

20. Questions I am representing my supervisor Dr. Krasic who was supposed to present the work. I will try as best as I can to answer all your questions. For further information, please contact Dr. Krasic: krasic@cs.ubc.ca http://qstream.org (all benchmark scripts and qstream source available open source) 20