http://www.napa-wine.eu

Effects of P2P Streaming

on Video Quality

Csaba Kiraly, Luca Abeni, Renato Lo CignoDISI – University of Trento, Italy

kiraly@disi.unitn.it

ICC 2010, Cape Town, 23-27 May 2010 2

Problem domainP2P Streaming, also known as P2P-TV Examples you might know

PPLive, SoapCast, TVAnts, etc. How they work?

A source generates encoded audio/video This media stream is divided into chunks Various peers receive the encoded media and

contribute to the diffusion, by forwarding received chunks to other peers

Live stream, so delay does matter!

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Studying chunk diffusion Numerous simulators are available to study these

systems P2PTVSim, PeerSim, SSSim, etc.

These provide answers like

0.8 Mb/s with 4% chunk loss ↔ 0.7 Mb/s with 2% loss

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Our Contribution Methodology and tools for the comparison of

P2P-TV systems through the evaluation of received video quality As seen by the user

Simulation driven by real video traces Instead of simplifying assumptions, like

“… lets assume the video is 1Mb/s CBR …”

Initial evaluation using the new tool Choice of encoding rate Confronting chunkization schemes Various codecs

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Methodology and Tools

P2P Simulator

overlay topologychunk rate and sizechunk and peer schedulers

chunk loss

Encoder

Chunkizer

Remove lost chunks

Fill missing frames

Compare

Raw video stream

chunk time and size trace

corrupted stream

refilled stream

chunks

PSNR, SSIM, etc.

• Codec• Encoding rate• GOP size• etc.

Chunk forming:• fixed size• 1 chunk = 1 GOP• 1 chunk = N frames

• Use codec’s error concealment• replicate last decoded frame

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Simulation parameters 1000 peers

Push based operation based on buffer map of neighbours Overlay

unstructured random regular graph overlay with degree 20

Network Access link constrained Homogeneous upload bandwidth of 1 Mb/s Download bandwidth is not a bottleneck

Raw stream: “foreman” sequence looped 4 times Encoding: H.264 using ffmpeg and x264

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Streaming rate vs. chunk loss

Curves became flat: Quality gained by increased encoding rate is lost

during transmission

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Blind vs. media-aware chunkization Comparing chunk creation policies

Blind: each chunk has same fix size, independent of stream structure

Media-aware: respect frame boundaries, e.g.1 chunk = 1 GOP (Group Of Pictures)

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The effect of schedulersComparing different

chunk and peer selection policies

a good scheduler ensures lossless

delivery with low delay

Guarantees unaffected PSNR to the users.

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Choosing the right codec Evaluated received video quality as a function of

video rate with 4 codecs

No real surprises H.263 < MPEG2 < MPEG4 < H.264

Slight differences in the optimal working point Because of different error concealment implementations

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Conclusions Simulating the P2P system and evaluating

the quality of video “as seen by users” is feasible

The proposed methodology allows joint evaluation of media encoding, chunkization strategies, and “traditional” peer parameters, such as scheduling and overlay algorithms

Tool-chain available as open source GPL code: http://napa-wine.eu

Questions?