© 2014 Networking for Information Communications and Energy Lab. Q17: IPTV and Netflix: How can the Internet Support Video? Prof. Hongseok Kim Networked Life: 20 Questions and Answers (M. Chiang, Princeton University)

2 Video watching is changing  Content type »User generated as well as licensed  When »DVR on IPTV, HBO Go …  Where »Anywhere with Internet connectivity  How »Almost any device

3 How much  Hulu : 31 million unique viewers in Feb  Comcast : 39 million, watching 205 million videos  US : 100 million IPTV users  YouTube and Netflix : half of Internet usage

4 classification1  Precoded »Vast majority is precoded »The content is already encoded and stored somewhere  Real time »Sports, news, weather Two way interactive −Online gaming −Video conferencing

5 classification2  Download  Streaming Netflix and YouTube »Device does not keep a local copy

6 classification3  Channelized »Follow the schedule of each channel accordingly −TV, DVR  On demand »VoD(Video on Demand) −YouTube, Netflix, some premium TV  NVoD »Near Video on Demand »Which staggers the same channel every few minutes, so that within a latency tolerance of that few minutes, you get the experience of VoD

7 classification4  Multicast Extreme form : broadcast »Everyone is in the multicast group  Unicast

8 IPTV  Over private and managed network, often with a set-top box on consumer premise  IP convergence Cost Flexibility compression

9 IPTV

10 VoI  Over public networks  Client-server without fee »YouTube, ABC and BBC  Client-server with fee »Netflix, Amazon Prime, Hulu Plus, HBO Go  P2P

11 VoI

12 Quality  Bit rate / distortion »Motion »Screen resolution »Viewing distance/screen size »Efficiency of compression »SD, HD, UltraHD  Delay  Jitter

13 Questions  How can the pipe take on so many bits per second?  How to keep track of video?  How to support quality of service over best effort network?

14 Layers

15 Video  Sequence of frames moving at a particular speed  Each frame is a picture consists of pixels  Each pixel is {colors, luminance} encoded in bits  Bit rate = bits per frame * number of frames per second

16 Compression  Remove redundancies in signals  Lossless compression Lempel-ziv  Lossy compression Tradeoff between compression ratio and resulting fidelity

17 Rate distortion curve

18 Which bitrate?  Distortion tolerable  Channel condition  Usage quota

19 What to compress  Redundancies Frame-to-frame similarities  Human visual limitations Transform coding  Statistical structures Huffman coding

20 Standards  MPEG1: 1992 »VCD, 1Mbps  MPEG2(H.262): 1996 »DVD, 10Mbps  MP3 »Standard for the online music industry »12:1 compression ratio  MPEG4: 2000  MPEG4 Part 10(H.264): 2004 »HDTV, 15-20Mbps, Blu-ray, 40Mbps  H.261, QuickTime, Windows, Media Player, Flash, Real Media…

21 Inter-frame prediction 

22 Metrics  Bitrate efficiency »If GoP longer, bit rate becomes lower  Error resilience »If an I frame lost  Instant channel change »For channelized video content, the ability to change channels fast is important

23 Example

24 I frame dropped 

25 P frame dropped 

26 B frame dropped 

27 Application layer  IGMP Membership-query Membership-report Leave-group(optional) Unicast help  SIP

28 RTSP

29 Transport layer  UDP Connectionless  Differences compared to TCP No congestion control No retransmission Latency vs. reliability(tradeoff)  RTP

30 Another use of UDP  Network management protocols SNMP RIP  Number of states and number of parallel sessions  Handshake and tear down overhead  Header overhead »8bytes(UDP)<20bytes(TCP)

31 Latency-jitter tradeoff

32 Optimization

33 Solution

34

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36 Summary  IP has become the basis of video content  Content being decoupled from delivery channels and devices  Quality of service provided through different mechanisms  Layering in action

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