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© 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)
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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
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3 How much Hulu : 31 million unique viewers in Feb. 2012 Comcast : 39 million, watching 205 million videos US : 100 million IPTV users YouTube and Netflix : half of Internet usage
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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
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5 classification2 Download Streaming Netflix and YouTube »Device does not keep a local copy
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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
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7 classification4 Multicast Extreme form : broadcast »Everyone is in the multicast group Unicast
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8 IPTV Over private and managed network, often with a set-top box on consumer premise IP convergence Cost Flexibility compression
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9 IPTV
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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
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11 VoI
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12 Quality Bit rate / distortion »Motion »Screen resolution »Viewing distance/screen size »Efficiency of compression »SD, HD, UltraHD Delay Jitter
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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?
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14 Layers
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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
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16 Compression Remove redundancies in signals Lossless compression Lempel-ziv Lossy compression Tradeoff between compression ratio and resulting fidelity
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17 Rate distortion curve
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18 Which bitrate? Distortion tolerable Channel condition Usage quota
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19 What to compress Redundancies Frame-to-frame similarities Human visual limitations Transform coding Statistical structures Huffman coding
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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…
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21 Inter-frame prediction
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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
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23 Example
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24 I frame dropped
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25 P frame dropped
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26 B frame dropped
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27 Application layer IGMP Membership-query Membership-report Leave-group(optional) Unicast help SIP
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28 RTSP
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29 Transport layer UDP Connectionless Differences compared to TCP No congestion control No retransmission Latency vs. reliability(tradeoff) RTP
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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)
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31 Latency-jitter tradeoff
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32 Optimization
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33 Solution
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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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Thank you! Networking Next Information Innovative Communications Creative Energy Envisioning
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