End-to-end encrypted collaborative documents, using Automerge and Signal

Dependencies

Setup dependencies

• docker

Benchmarking dependencies

See Dockerfile

Plotting dependencies

• uv

Usage

Build and setup

docker-compose up --build -d
./netprofile.sh [slow|fast|off] # Sets latency and bandwidth in container
docker exec -it e2ee-cd /bin/bash  # Open shell in 

Benchmark

1. Start the signal-cli daemon with

signal-cli --config=./signal-data/signal-multiaccount daemon --http  

If you want to run the benchmark for only one user, use

signal-cli --config=./signal-data/signal-multiaccount -a=$NUMBER daemon --http 

For usability, you might want to source .env, which exports the variables ACCOUNT_1 and ACCOUNT_2.

1. If you get a warning WARN MultiAccountManager - Ignoring $NUMBER: User is not registered. (NotRegisteredException): register the signal number as follows (see signal-cli Wiki):

 signal-cli --config=./signal-data/signal-multiaccount link -n "${OPTIONAL_DEVICE_NAME} | tee >(xargs -L 1 qrencode -t utf8)

Then scan the QR code with a primary device where you are already logged in with the Signal account for $NUMBER. Alternatively, if your device does not recognize the QR code shown by qrencode, get the link by running signal-cli --config=./signal-data/signal-multiaccount link -n "${OPTIONAL_DEVICE_NAME}" and paste the sgnl://linkdevice?uuid=... link in your favorite QR code generator (e.g., search for "qr code for $LINK" on DuckDuckGo).

2. In another tab, cd crdt-benchmarks/benchmarks/automerge and run npm start to run all benchmarks.

   To run a specific benchmark, run npm start -- $BENCH_NAME, where $BENCH_NAME is one of b1-signal, b2-signal, b3-signal.

Benchmarking

1. Build the Docker image with docker-compose up --build -d

Generating the plots

We use uv to manage Python dependencies. To run the Jupyter notebooks, run the following command to automatically read the data in benchmark_data and generate plots in benchmark_plots.

uv run --with jupyter jupyter execute analysis-1.ipynb
uv run --with jupyter jupyter execute analysis_2-3.ipynb

Alternatively, make sure that you have the correct python version specified in .python-version, install the dependencies listed in pyproject.toml along with jupyter using your favourite python package manager, and launch jupyter.