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Trevi

An implementation of a streaming RLNC forward error correction code, inspired by:

Wunderlich, S., Gabriel, F., Pandi, S., Fitzek, F. H., & Reisslein, M. (2017). Caterpillar RLNC (CRLNC): A Practical Finite Sliding Window RLNC Approach. IEEE Access, 5, 20183-20197.

This early implementation is very crude, but results should be the same as stated in the paper.

The code is not really optimized, processing time on my old i7 based laptop are of this order of magnitude (encoding window size=32, decoding window size=64) :

Operation processing time (usec)
Encoding 152.311
Decoding 53.6886

Implementation principle

TODO

Current implementation limitations

Encoding window size is limited to 32 (coded packet composition are encoded as a bitfield on a uint32) before being sent to the decoder. Decoding window size can be arbitrarily large, but must be strictly superior to the encoding window size (33 if encoding window size is 32, for example).

Getting Started

Prerequisites

This is a C++ project. Only tested on Linux for now. You will need CMake to compile it properly. Also you will need an SSE3 capable CPU to run it (not sure if mandatory).

Compiling

Using CMake out of source compilation:

(in trevi source directory)

mkdir build
cd build
cmake ..
make

There are also several compilation options, to enable/disable profiling, etc. Just check using ccmake or other cmake UI tools.

Example applications

There is no real API documentation for trevi (apart from the comments in trevi.h, for now !) but several example applications are provided

UDP loss recovery

Two projects are provided, aimed at simulation UDP packet loss and recovery using trevi. I use them to test reliability of x264/RTP streaming over a lossy UDP channel.

trevi_tx

This application grabs packets from an UDP port, encodes them and writes the output packets to another UDP port. Check the "usage" option of this application to get more details:

usage: ./examples/tx/trevi_tx [options] ... 
options:
  -i, --input_port      UDP port for input data (int [=5000])
  -o, --output_port     UDP port for encoded output data (int [=5001])
  -h, --output_host     address of destination host for encoded data (string [=127.0.0.1])
  -e, --window_size     Encoding window size (must be inferior or equal to 32) (int [=32])
  -s, --nsrc_blocks     Number of source block after which we send code blocks (int [=1])
  -c, --ncode_blocks    Number of coded blocks to send after processing nsrc_blocks (int [=1])
  -p, --loss_proba      Simulated random uniform packet loss probability (float [=0])
  -?, --help            print this message

As you can see, if you want to simulate a lossy channel, this is where you specify the loss parameter.

trevi_rx

This application grabs packets from an UDP port, decodes them and writes the output decoded packets to another UDP port. Check the "usage" option of this application to get more details:

usage: ./examples/rx/trevi_rx [options] ... 
options:
  -i, --input_port     UDP port for encoded input data (int [=5001])
  -o, --output_port    UDP port for decoded output data (int [=5002])
  -h, --output_host    address of destination host for decoded data (string [=127.0.0.1])
  -d, --window_size    Decoding window size (must be strictly superior to encoding window size) (int [=64])
  -?, --help           print this message

Testing Trevi for reliable x264/RTP video streaming

You can quickly test Trevi for reliable video streaming over lossy channels using both trevi_tx and trevi_rx, along with a simple gstreamer setup.

Setting Trevi encoder and decoder

First, launch trevi_tx:

./examples/tx/trevi_tx -p 0.1

This will launch the encoder listening on port 5000 for input data, and outputing encoded data on port 5001 (localhost), simulating a uniform packet loss of probability 0.1 (10% loss):

nicolas@xxxx:~/dev/trevi/build$ ./examples/tx/trevi_tx -p 0.1
Starting Trevi UDP encoder: 
UDP input port for input data: 			5000
UDP output for encoded data: 			127.0.0.1:5001
Simulated channel loss probability: 			0.1

Then, also launch the decoder, trevi_rx:

./examples/rx/trevi_rx

This will launch the decoder, with default parameters:

nicolas@xxxx:~/dev/trevi/build$ ./examples/rx/trevi_rx 
Starting Trevi UDP decoder: 
UDP input port for encoded data: 			5001
UDP output for decoded data: 			127.0.0.1:5002
Setting gstreamer UDP streaming and output visualization

First, launch the x264 streaming, for example:

gst-launch-1.0 v4l2src ! x264enc bitrate=3000 tune=zerolatency ! rtph264pay pt=96 mtu=512 ! udpsink host=127.0.0.1 port=5000

This will start streaming the webcam on port 5000 (localhost), using an h264 encoder (bitrate 3Mbit/s). MTU size is not important, but for debug purposes, I usually use 512 or 1024 bytes.

Then, start the visualization gstreamer pipeline:

gst-launch-1.0 udpsrc port=5002 caps ='application/x-rtp, media=(string)video, clock-rate=(int)90000, encoding-name=(string)H264' ! rtph264depay ! decodebin ! autovideosink sync=false

This gstreamer pipeline will display the Trevi-decoded video grabbed from port 5002, in a graphical window.

Benchmark application

There is also a benchmark application that should be able to replicate several results of the original paper. You can test various parameters, such as:

  • Encoding window size
  • Decoding window size
  • Simulated Gilbert-Elliot loss model parameters

Just launch trevi_bench to test various parameters. If everything goes well, you should be able to reproduce the results from the paper:

./examples/bench/trevi_bench

Usage:

usage: ./examples/bench/trevi_bench [options] ... 
options:
  -e, --encoding_window_size     Encoding window size (must be inferior or equal to 32) (int [=32])
  -d, --decoding_window_size     Decoding window size (must be strictly superior to encoding window size) (int [=64])
  -s, --nsrc_blocks              Number of source block after which we send code blocks (int [=1])
  -c, --ncode_blocks             Number of coded blocks to send after processing nsrc_blocks (int [=1])
  -b, --bad_state_proba          Simulated loss - steady state probability for the bad state of Gilbert-Elliot model (float [=0.05])
  -B, --expected_burst_length    Simulated loss - expected sojourn time in the bad state (ie. error burst length) (float [=4])
  -?, --help                     print this message

Example output:

current source packets processed: 100000
Average decode processing time = 131.886 microsec.
Average encode processing time = 45.6679 microsec.
Channel packet loss: 20371 / 100000 Channel loss probability: 20.371%
Packets unrecovered: 209 / 100000 - Packet loss probability: 0.209%
(Average delay - decoding_window_size) (in slots): 1.47159

Credits

Christopher Taylor (catid) for his Galois Field arithmetic implementation Logging provided by loguru Awesome profiling using dollar

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