Presentation is loading. Please wait.

Presentation is loading. Please wait.

How to Meet the Deadline for Packet Video Bernd Girod Mark Kalman Eric Setton Information Systems Laboratory Stanford University.

Published by Modified over 9 years ago

Similar presentations

Presentation on theme: "How to Meet the Deadline for Packet Video Bernd Girod Mark Kalman Eric Setton Information Systems Laboratory Stanford University."— Presentation transcript:

1 How to Meet the Deadline for Packet Video Bernd Girod Mark Kalman Eric Setton Information Systems Laboratory Stanford University

2 2 B. Girod: Packet Video 2006 [Economist, September 2005] THE MEANING OF FREE SPEECH The acquisition by eBay of Skype is a helpful reminder to the world's trillion- dollar telecoms industry that all phone calls will eventually be free...... Ultimately—perhaps by 2010—voice may become a free internet application, with operators making money from related internet applications like IPTV... THE MEANING OF FREE SPEECH The acquisition by eBay of Skype is a helpful reminder to the world's trillion- dollar telecoms industry that all phone calls will eventually be free...... Ultimately—perhaps by 2010—voice may become a free internet application, with operators making money from related internet applications like IPTV...

3 3 B. Girod: Packet Video 2006 IPTV is Becoming a Reality SBC (ATT) 18M IPTV households by 2007 SBC (ATT) 18M IPTV households by 2007 Verizon 10M IPTV households by 2009 Verizon 10M IPTV households by 2009 [IEEE Spectrum, Jan. 2005]

4 4 B. Girod: Packet Video 2006 Why Is Internet Video Hard? Internet is a best-effort network... CongestionInsufficient rate to carry all traffic Packet lossImpairs perceptual quality DelayImpairs interactivity of services; Zapping < 500 ms

5 5 B. Girod: Packet Video 2006 How to Meet the Deadline for Packet Video

6 6 B. Girod: Packet Video 2006 Internet How to Meet the Deadline for Packet Video

7 7 B. Girod: Packet Video 2006 How to Meet the Deadline for Packet Video Congestion, QoS, and “fair” sharing Maximum-utility resource allocation for multiple video streams Example: video over wireless home networks Congestion-distortion optimized packet scheduling (CoDiO) Example: P2P multicasting of live video Packet scheduling for multicast trees

8 8 B. Girod: Packet Video 2006 Measuring Congestion Traffic flow E[Delay] “Congestion” Congestion in packet-switched network: queuing delay that packets experience, weighted by size of the packet averaged over all packets in the network

9 9 B. Girod: Packet Video 2006 Congestion Grows Nonlinearly with Link Utilization Congestion  [seconds] Rate R C

10 10 B. Girod: Packet Video 2006 How 1B Users Share the Internet maximum transfer unit round trip time packet loss rate data rate [Mahdavi, Floyd, 1997] [Floyd, Handley, Padhye, Widmer, 2000] Rate R Growing congestion p 0.0010.00010.10.01 TCP Throughput

11 11 B. Girod: Packet Video 2006 QoS vs. Best Effort Reservation-ism –Voice and video need guaranteed QoS (bandwidth, loss, delay) –Requires admission control: “Busy tone” when network is full –Best effort is fine for data applications Best Effort-ism –Best Effort good enough for all applications –Real-time applications can be made adaptive to cope with any level of service –Overprovisioning always solves the problem, and it’s cheaper than QoS guarantees

12 12 B. Girod: Packet Video 2006 Simple Model of A Shared Link Link of capacity C is shared among k flows Fair sharing: each admitted flow uses rate R=C/k Homogeneous flows with same utility function u(R) Total utility C [Breslau, Shenker, 1998]

13 13 B. Girod: Packet Video 2006 Rigid Applications Utility u=0 below of minimum bit-rate B Admit at most flows With sufficient overprovisioning, no admission control needed, since u C/k B 1

14 14 B. Girod: Packet Video 2006 Elastic Applications Elastic applications: convex utility function u(R) All flows should be admitted: best effort! R u(R)u(R)

15 15 B. Girod: Packet Video 2006 QoS vs. Best Effort for Video H.264 video coding for 2 different testsequences Video is elastic application... above a certain minimum quality Bottleneck links: admission control and dynamic rate control combined Rate must be adapted to network throughput. How? Utility function depends on content: should use unequal rate allocation Foreman Mobile Good picture quality Bad picture quality

16 16 B. Girod: Packet Video 2006 Better than utility-oblivious “ fair ” sharing With r k >=0  Karush-Kuhn-Tucker conditions Different Utility Functions rkrk ukuk Equal-slope “Pareto condition” Vilfredo Pareto 1848-1923

17 17 B. Girod: Packet Video 2006 Distribution of TV over WLAN [courtesy: van Beek, 2004] 5 Mbps 2 Mbps 11 Mbps Home Media Gateway

18 18 B. Girod: Packet Video 2006 Video over WLAN Decoder Transcoder Controller 802.11b Wireless Terminal Network Interface playout buffer Video encoded at higher rate Receiver [Kalman, van Beek, Girod 2005]

19 19 B. Girod: Packet Video 2006 Video over WLAN with Multiple Streams Decoder Transcoder Controller Wireless terminals Network Interface Transcoder … … … Decoder … c0c0 c1c1 cMcM 0 1 M 0 1 M Receiver (Multi-Channel) [Kalman, van Beek, Girod 2005]

20 20 B. Girod: Packet Video 2006 Dynamic Estimation of R-D Curve Parameters track weighted average of last I-Frame, P-Frame and B-Frame Scene cuts [ Stuhlmüller et al. 2000 ] R-D Model Rate 

21 21 B. Girod: Packet Video 2006 802.11b Transmission of 2 Video Streams Link rates [kbps] Channel time allocation Transcoder bit-rate [kbps] Backlog in frames PSNR in dB

22 22 B. Girod: Packet Video 2006 Video Distortion with Self Congestion Good Picture quality Bad picture quality Bit-Rate [kbps] Self congestion causes late loss

23 23 B. Girod: Packet Video 2006 Effect of Playout Delay and Loss Sensitivity ForemanSalesman Simulations over ns-2 Link capacity 400 kb/s Simulations over ns-2 Link capacity 400 kb/s 40% headroom 10%

24 24 B. Girod: Packet Video 2006 1 sender 380 kbps, 36 dB Highest sustainable video quality 420 kbps, 33.7 dB Simulation of 600 kbps link Latency 400 msec

25 25 B. Girod: Packet Video 2006 Modeling Self-Congestion for Packet Scheduling Probability distribution delay Rate-distortion optimized packet scheduling (RaDiO) typically assumes independent delay pdfs for successive packet transmissions [Chou, Miao, 2001] Model delay pdf by exponential with varying shift [Setton, Girod, 2004]

26 26 B. Girod: Packet Video 2006 CoDiO Light Scheduler I BB B P B IB B P Pictures to send Schedule IP BB B PI B B BI B

27 27 B. Girod: Packet Video 2006 CoDiO Scheduling Performance Simulations over ns-2 Packet loss rate 2% Bandwidth 400 kb/s Propagation delay: 50ms Simulations over ns-2 Packet loss rate 2% Bandwidth 400 kb/s Propagation delay: 50ms 30 % 25 % Mother & DaughterNews Playout deadline (s)

28 28 B. Girod: Packet Video 2006 H.264/AVC @250 kb/s Link rate 400 kb/s, propagation delay 50 ms 2 % packet loss 0.6 second playout deadline CoDiO ARQ

29 29 B. Girod: Packet Video 2006 Sequence: Foreman Packet loss rate 2% Link capacity 400 kb/s Propagation delay: 50ms Sequence: Foreman Packet loss rate 2% Link capacity 400 kb/s Propagation delay: 50ms 60 % Playout deadline (s) CoDiO vs. RaDiO

30 30 B. Girod: Packet Video 2006 Video Multicast over P2P Networks Challenges Limited bandwidth Delay due to multi-hop transmission Unreliability of peers Our Approach [Setton, Noh, Girod, 2005] Determine encoding rate as a function of network bandwidth Build and maintain complementary multicast trees Adapt media scheduling to network conditions and to content Request retransmissions to mitigate losses Related work [Chu, Rao, Zhang, 2000] [Padmanabhan, Wang and Chou, 2003] [Guo, Suh, Kurose, Towsley, 2003] [Cui, Li, Nahrstedt, 2004] [Do, Hua, Tantaoui, 2004] [Hefeeda, Bhargava, Yau, 2004] [Zhang, Liu, Li and Yum, 2005] [Zhou, Liu, 2005] [Chi, Zhang, Packet Video 2006] … … Video stream

31 31 B. Girod: Packet Video 2006 Experimental Setup Network/protocol simulation in ns-2 –300 active peers –Random peer arrival/departure average life-time 5 minutes –Over-provisioned backbone –Typical access rate distribution –Delay: 5 ms/link + congestion Video streaming –H.264/AVC encoder @ 250 kb/s –15 minute live multicast [Sripanidkulchai et al., 2004] Downlink UplinkPercentage 512 kb/s256 kb/s 56% 3 Mb/s384 kb/s 21% 1.5 Mb/s896 kb/s 9% 20 Mb/s 2 Mb/s 3% 20 Mb/s 5 Mb/s 11% Downlink UplinkPercentage 512 kb/s256 kb/s 56% 3 Mb/s384 kb/s 21% 1.5 Mb/s896 kb/s 9% 20 Mb/s 2 Mb/s 3% 20 Mb/s 5 Mb/s 11% [Setton, Noh, Girod, 2005]

32 32 B. Girod: Packet Video 2006 Join and Rejoin Latencies Simulations over ns-2, 300 peers Number of trees: 4 Retransmissions enabled Simulations over ns-2, 300 peers Number of trees: 4 Retransmissions enabled [Setton, Noh, Girod, 2005]

33 33 B. Girod: Packet Video 2006 CoDiO retransmissions No retransmissions P2P Video Multicast: 64 out of 300 Peers H.264 @ 250 kb/s 2 second playout deadline for all streams

34 34 B. Girod: Packet Video 2006 P2P Video Multicast: 64 out of 300 Peers H.264 @ 250 kb/s 2 second playout deadline for all streams CoDiO retransmissions No retransmissions

35 35 B. Girod: Packet Video 2006 CoDiO Scheduling for Multicast Trees Parent PI BP B P B DIDI DBDB D P3 D P2 D P1 DBDB DBDB [Setton, Noh, Girod, 2006] Child

36 36 B. Girod: Packet Video 2006 Gain by Multicast CoDiO Simulations over ns-2, 300 peers Number of trees: 4 Retransmissions enabled Simulations over ns-2, 300 peers Number of trees: 4 Retransmissions enabled 30 % 40 % Foreman Mother & Daughter Playout deadline (s) [Setton, Noh, Girod, 2006]

37 37 B. Girod: Packet Video 2006 Sender-driven CoDiO light 33.71 dB Without prioritization 30.17 dB H.264 @ 250 kb/s 0.8 second playout deadline for all streams Average Video Sequence for 75 Peers

38 38 B. Girod: Packet Video 2006 Conclusions Must avoid congestion for low latency Video streaming over bottlenecks (IPTV, WLAN... ): combine admission control and rate control R-D-aware rate allocation better than fair sharing Packet scheduling should consider congestion rather than rate Low-complexity CoDiO scheduler P2P video multicast possible with low latency Retransmissions effective with application-layer multicast CoDiO extended to packet scheduling for multicast trees Cross-layer paradigm Media-aware transport  superior system performance

39 The End http://www.stanford.edu/~bgirod/publications.html

Download ppt "How to Meet the Deadline for Packet Video Bernd Girod Mark Kalman Eric Setton Information Systems Laboratory Stanford University."

Similar presentations

Streaming Video over the Internet

Streaming Video over the Internet
Playback-buffer Equalization For Streaming Media Using Stateless Transport Prioritization By Wai-tian Tan, Weidong Cui and John G. Apostolopoulos Presented.

Playback-buffer Equalization For Streaming Media Using Stateless Transport Prioritization By Wai-tian Tan, Weidong Cui and John G. Apostolopoulos Presented.
Doc.: IEEE 802.11-14/0604r1 Submission May 2014 Slide 1 Modeling and Evaluating Variable Bit rate Video Steaming for 802.11ax Date: 2014-05-12 Authors:

Doc.: IEEE /0604r1 Submission May 2014 Slide 1 Modeling and Evaluating Variable Bit rate Video Steaming for ax Date: Authors:
2005/12/06OPLAB, Dept. of IM, NTU1 Optimizing the ARQ Performance in Downlink Packet Data Systems With Scheduling Haitao Zheng, Member, IEEE Harish Viswanathan,

2005/12/06OPLAB, Dept. of IM, NTU1 Optimizing the ARQ Performance in Downlink Packet Data Systems With Scheduling Haitao Zheng, Member, IEEE Harish Viswanathan,
Distributed Control Algorithms for Service Differentiation in Wireless Packet Networks Michael Barry, Andrew T Campbell, Andras Veres

Distributed Control Algorithms for Service Differentiation in Wireless Packet Networks Michael Barry, Andrew T Campbell, Andras Veres
Receiver-driven Layered Multicast S. McCanne, V. Jacobsen and M. Vetterli University of Calif, Berkeley and Lawrence Berkeley National Laboratory SIGCOMM.

Receiver-driven Layered Multicast S. McCanne, V. Jacobsen and M. Vetterli University of Calif, Berkeley and Lawrence Berkeley National Laboratory SIGCOMM.
Presented by Scott Kristjanson CMPT-820 Multimedia Systems Instructor: Dr. Mohamed Hefeeda 1 Cross-Layer Wireless Multimedia.

Presented by Scott Kristjanson CMPT-820 Multimedia Systems Instructor: Dr. Mohamed Hefeeda 1 Cross-Layer Wireless Multimedia.
Contention Window Optimization for IEEE 802.11 DCF Access Control D. J. Deng, C. H. Ke, H. H. Chen, and Y. M. Huang IEEE Transaction on Wireless Communication.

Contention Window Optimization for IEEE DCF Access Control D. J. Deng, C. H. Ke, H. H. Chen, and Y. M. Huang IEEE Transaction on Wireless Communication.
Measurements of Congestion Responsiveness of Windows Streaming Media (WSM) Presented By:- Ashish Gupta.

Measurements of Congestion Responsiveness of Windows Streaming Media (WSM) Presented By:- Ashish Gupta.
Advances in Network-adaptive Video Streaming Bernd Girod J. Chakareski, M. Kalman, Y. J. Liang, E. Setton, R. Zhang Information Systems Laboratory Department.

Advances in Network-adaptive Video Streaming Bernd Girod J. Chakareski, M. Kalman, Y. J. Liang, E. Setton, R. Zhang Information Systems Laboratory Department.
Presented by Santhi Priya Eda Vinutha Rumale.  Introduction  Approaches  Video Streaming Traffic Model  QOS in WiMAX  Video Traffic Classification.

Presented by Santhi Priya Eda Vinutha Rumale.  Introduction  Approaches  Video Streaming Traffic Model  QOS in WiMAX  Video Traffic Classification.
Resilient Peer-to-Peer Streaming Paper by: Venkata N. Padmanabhan Helen J. Wang Philip A. Chou Discussion Leader: Manfred Georg Presented by: Christoph.

Resilient Peer-to-Peer Streaming Paper by: Venkata N. Padmanabhan Helen J. Wang Philip A. Chou Discussion Leader: Manfred Georg Presented by: Christoph.
Receiver-driven Layered Multicast S. McCanne, V. Jacobsen and M. Vetterli SIGCOMM 1996.

Receiver-driven Layered Multicast S. McCanne, V. Jacobsen and M. Vetterli SIGCOMM 1996.
Streaming Video over the Internet: Approaches and Directions Dapeng Wu, Yiwei Thomas Hou et al. Presented by: Abhishek Gupta

Streaming Video over the Internet: Approaches and Directions Dapeng Wu, Yiwei Thomas Hou et al. Presented by: Abhishek Gupta
Bernd Girod. Joint Source-Network Coding for Real-time Media 1 Joint Source-Network Coding for Real-time Media Bernd Girod Information Systems Laboratory.

Bernd Girod. Joint Source-Network Coding for Real-time Media 1 Joint Source-Network Coding for Real-time Media Bernd Girod Information Systems Laboratory.
CStream: Neighborhood Bandwidth Aggregation For Better Video Streaming Thangam Vedagiri Seenivasan Advisor: Mark Claypool Reader: Robert Kinicki 1 M.S.

CStream: Neighborhood Bandwidth Aggregation For Better Video Streaming Thangam Vedagiri Seenivasan Advisor: Mark Claypool Reader: Robert Kinicki 1 M.S.
Rate Distortion Optimized Streaming Maryam Hamidirad CMPT 820 Simon Fraser Univerity 1.

Rate Distortion Optimized Streaming Maryam Hamidirad CMPT 820 Simon Fraser Univerity 1.
A Quality-Driven Decision Engine for Live Video Transmission under Service-Oriented Architecture DALEI WU, SONG CI, HAIYAN LUO, UNIVERSITY OF NEBRASKA-LINCOLN.

A Quality-Driven Decision Engine for Live Video Transmission under Service-Oriented Architecture DALEI WU, SONG CI, HAIYAN LUO, UNIVERSITY OF NEBRASKA-LINCOLN.
Introduction Future wireless systems will be characterized by their heterogeneity - availability of multiple access systems in the same physical space.

Introduction Future wireless systems will be characterized by their heterogeneity - availability of multiple access systems in the same physical space.
ACM Multimedia October 4, 2001 Real-time Voice Communication over the Internet Using Packet Path Diversity Yi Liang, Eckehard Steinbach, and Bernd Girod.

ACM Multimedia October 4, 2001 Real-time Voice Communication over the Internet Using Packet Path Diversity Yi Liang, Eckehard Steinbach, and Bernd Girod.

Similar presentations

Ads by Google