Transport of Real-Time Traffic over the Internet Bernd Girod Information Systems Laboratory Stanford University

2 B. Girod: Internet Real-Time Transport, September 2005 [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 B. Girod: Internet Real-Time Transport, September 2005 IPTV Rollout IPTV SBC 18M households by 2007 IPTV SBC 18M households by 2007 Verizon 10M households by 2009 Verizon 10M households by 2009 [IEEE Spectrum, Jan. 2005]

4 B. Girod: Internet Real-Time Transport, September 2005 Why Is Real-Time Transport Hard? Internet is a best-effort network... CongestionInsufficient rate to communicate Packet lossImpairs perceptual quality DelayImpairs interactivity of services; Telephony: one way delay < 150 ms [ITU-T Rec. G.114] Delay jitter Obstructs continuous media playout

5 B. Girod: Internet Real-Time Transport, September 2005 Outline of the Talk QoS vs. best effort Resource allocation for IPTV Rate-distortion optimized streaming Multi-path routing P2P multicasting of live video streams

6 B. Girod: Internet Real-Time Transport, September 2005 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 TCP Throughput

7 B. Girod: Internet Real-Time Transport, September 2005 QoS vs. Best Effort Reservation-ism –Voice and video need guaranteed QoS (bandwidth, loss, delay) –Implement 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

8 B. Girod: Internet Real-Time Transport, September 2005 Simple Model of A Shared Link Link of capacity C is shared among k flows Fair sharing: each flow uses data rate C/k Homogeneous flows with same utility function u(.) Total utility C [Breslau, Shenker, 1998]

9 B. Girod: Internet Real-Time Transport, September 2005 Rigid Applications Utility u=0 below of minimum bit-rate B Maximum total utility U=k* is achieved by admitting at most k* flows u C/k B 1 [Breslau, Shenker, 1998]

10 B. Girod: Internet Real-Time Transport, September 2005 Rigid Applications (cont.) Expected loss in total utility w/o admission control Gap  U is substantial when number of admissable flows k* is small Gap  U usually disappears with growing capacity C  Overprovisioning can solve the problem! [Breslau, Shenker, 1998]

11 B. Girod: Internet Real-Time Transport, September 2005 Elastic Applications Elastic applications: utility function u(k), such that total utility U(k)=ku(C/k) increases with k Example: u(C/k)=1-a C/k All flows should be admitted: best effort! C/k u

12 B. Girod: Internet Real-Time Transport, September 2005 Video Compression H.264 video coding for 2 different testsequences Video is elastic application Rate must be adapted to network throughput How to achieve rate control for stored content or multicasting? Utility function depends on content: should use unequal rate allocation Foreman Mobile Good picture quality Bad picture quality

13 B. Girod: Internet Real-Time Transport, September 2005 Example: u k (r k )=1-a k r k With r k >=0  Karush-Kuhn-Tucker conditions ( “ reverse water-filling ” ) Better than utility-oblivious “ fair ” sharing Different Utility Functions rkrk ukuk Equal-slope “Pareto condition” Vilfredo Pareto

14 B. Girod: Internet Real-Time Transport, September 2005 Distribution of IPTV over WLAN [courtesy: van Beek, 2004] 5 Mbps 2 Mbps 11 Mbps Home Media Gateway

15 B. Girod: Internet Real-Time Transport, September 2005 Receiver (Multi-Channel) Transcoder Decoder Controller Video Streaming Over Shared Channel [Kalman, van Beek, Girod 2005]

16 B. Girod: Internet Real-Time Transport, September 2005 Tx Backlog for 4 Video Streams 85% WLAN Utilization [Kalman, van Beek, Girod 2005]

17 B. Girod: Internet Real-Time Transport, September 2005 Streaming of Stored Content DSL Cable wireless Media files are already compressed: How can we nevertheless adapt to network? 100s to 1000s simultaneous streams Server Client Network

18 B. Girod: Internet Real-Time Transport, September 2005 Not All Packets are Equally Important PPI I BBBPPPI I BBBP A … … … A…

19 B. Girod: Internet Real-Time Transport, September 2005 PBPPI I BBPPI I BBBP A … … … A… Not All Packets are Equally Important

20 B. Girod: Internet Real-Time Transport, September 2005 Distortion-Aware Packet Dropping Good Picture quality Bad picture quality Percentage of Packets Retained [%] Distortion aware Packet dropping No retransmissions QCIF Carphone I-P-P-P-P-P-... Oblivious [Chakareski, Girod, ICME 2004]

21 B. Girod: Internet Real-Time Transport, September 2005 Rate-Distortion Optimized (RaDiO) Streaming “Decide which packets to send (and when) to maximize picture quality while not exceeding an average rate” [2001] Server Client Request stream Rate-distortion preamble Packet schedule Video data Repeat request Repeat request Repeat request Network

22 B. Girod: Internet Real-Time Transport, September 2005 A Brief History of Media Streaming 1)Media streaming w/o congestion avoidance: “reckless driving” [1995] 2)TCP-friendly rate control: “Limit average rate for fair sharing with TCP” [1997] 3)Rate-distortion optimized packet scheduling (RaDiO): “Decide which packets to send (and when) to maximize picture quality while not exceeding an average rate” [2001] 4)Congestion-distortion-optimized scheduling/routing (CoDiO): “Decide which packets to send (and when) to maximize picture quality while minimizing network congestion.” [2004]

23 B. Girod: Internet Real-Time Transport, September 2005 Congestion vs. Rate Congestion: queuing delay that packets experience –weighted by size of the packet –averaged over all packets in the network Congestion increases nonlinearly with link bit-rate Congestion  [seconds] Rate R R max

24 B. Girod: Internet Real-Time Transport, September 2005 Video Distortion with Self Congestion Good Picture quality Bad picture quality Bit-Rate [kbps] Self congestion causes late loss

25 B. Girod: Internet Real-Time Transport, September 2005 Streaming with Last Hop Bottleneck Random cross traffic Low bandwidth last hop Video traffic Acknowledgments High bandwidth links

26 B. Girod: Internet Real-Time Transport, September 2005 Delay distribution Overall delay distribution Queue length determines delay of last hop delay pdf C

27 B. Girod: Internet Real-Time Transport, September 2005 Comparison RaDiO vs. CoDiO Simulations using H.263+ Rate : 10 fps Sequence : Foreman (32kbps,32kbps) Sequence length : 60s Playout deadline : 600ms 50 % PSNR [dB] Rate [kbps] PSNR [dB] End-to-end delay [ms]

28 B. Girod: Internet Real-Time Transport, September 2005 How To Avoid Traffic Jams? Avoid congested times...  Congestion-aware packet scheduling Avoid congested roads...  Congestion-aware routing

29 B. Girod: Internet Real-Time Transport, September 2005 Multipath Routing for Minimum Congestion 77 16kbps kbps Mesh network, fully connected Streaming 100 kbps from Node 1 to Node 5 Random cross traffic

30 B. Girod: Internet Real-Time Transport, September 2005 Multipath Video Streaming 6 dB Sequence : Foreman QCIF, 250 frames, 30 fps Codec: H.26L TML 8.5 Playout deadline : 500 ms Packetization : 1 frame/packet Traffic model: CBR No. of realizations: 400 Good Picture quality Bad picture quality Bit-Rate [kbps]

31 B. Girod: Internet Real-Time Transport, September 2005 Multipath Video Streaming 1 path 80 kbps, PSNR 32.5 dB 3 paths 187 kbps, PSNR 36.2 dB

32 B. Girod: Internet Real-Time Transport, September 2005 Distribution of Live Streams via “Pseudo-Multicast” Example AOL webcast of Live 8 concert July 2, 2005 Content delivery network... Splitter servers Media server 1500 servers in 90 locations 50 Gbps 175,000 simultaneous viewers 8M unique viewers

33 B. Girod: Internet Real-Time Transport, September 2005 P2P live multicast Content delivery network... Splitter servers 1500 servers in 90 locations 50 Gbps Distribution of Live Streams via “Pseudo-Multicast” Example AOL webcast of Live 8 concert July 2, 2005 Media server 175,000 simultaneous viewers 8M unique viewers 300 kbps

34 B. Girod: Internet Real-Time Transport, September 2005 P2P Multicast over 1 Tree

35 B. Girod: Internet Real-Time Transport, September 2005 P2P Multicast over 2 Trees

36 B. Girod: Internet Real-Time Transport, September 2005 P2P Ungraceful Parent Leave 3 trees Parent of yellow tree is down Hello, Yellow Tree Parent? Parent leave is detected Retransmissions requested New parent is selected Yellow tree is recovered

37 B. Girod: Internet Real-Time Transport, September 2005 Experimental Set-up Network/protocol simulation in ns-2 –1000 nodes –300 active peers –Random peer arrival/departure: ON (5 min)/OFF (30 s) –Over-provisioned backbone –Typical access bandwidth distribution –Delay: 5 ms/link + congestion Video streaming –Compression H.264 at 220 kbps –15 minute live multicast [Setton, Noh, Girod, ACM MM 2005]

38 B. Girod: Internet Real-Time Transport, September 2005 Join and Rejoin Latencies [Setton, Noh, Girod, ACM MM 2005]

39 B. Girod: Internet Real-Time Transport, September 2005 Congestion-Distortion Optimized P2P Live Streaming % peers connected to 4/4 trees [Setton, Noh, Girod, ACM MM 2005] With CoDiO Without CoDiO

40 B. Girod: Internet Real-Time Transport, September 2005 Congestion-distortion optimized (CoDiO) streaming Without CoDiO P2P Video Multicast: 64 out of 300 Peers 220 kbps 2 sec latency for all streams

41 B. Girod: Internet Real-Time Transport, September 2005 Concluding Remarks Over-provisioning makes QoS superfluous Elastic applications don’t need QoS Joint rate control for access bottlenecks (e.g. IPTV, WLAN) Media-aware congestion control (e.g. CoDiO) Multipath routing to mitigate congestion P2P viable alternative for content delivery networks Client-server  edge-based  P2P

The End