nomos-simulations/deprecated/mixnet-overall

NomMix Simulation

• Project Structure
• Features
• Future Plans
• Installation
• Getting Started

Project Structure

• cmd: CLIs to run the simulation and analyze the results.
• sim: Simulation that runs the NomMix defined in the protocol package.
• protocol: Core NomMix protocol implementation, which is going to be moved to the nomos-repos repository once verified by simulations.
• framework: Asynchronous framework that provides essential async functions for simulations and tests, implemented with various async libraries (asyncio, μSim, etc.)

Features

• NomMix protocol simulation
• Performance measurements
  • Bandwidth usages
  • Message dissemination time
• Privacy property analysis
  • Message sizes
  • Node states and hamming distances

Future Plans

• More NomMix features
  • Temporal mixing
  • Level-1 noise
• Adversary simulation to measure the robustness of NomMix

Installation

Clone the repository and install the dependencies:

git clone https://github.com/logos-co/nomos-simulations.git
cd nomos-simulations/mixnet
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Getting Started

Copy the config.ci.yaml file and adjust the parameters to your needs. Each parameter is explained in the config file. For more details, please refer to the documentation.

Run the simulation with the following command:

python -m cmd.main --config {config_path}

All results are printed in the console as below. And, all plots are shown once all analysis is done.

Spawning node-0 with 3 conns
Spawning node-1 with 3 conns
Spawning node-2 with 3 conns
Spawning node-3 with 3 conns
Spawning node-4 with 3 conns
Spawning node-5 with 3 conns
==========================================
Message Dissemination Time
==========================================
[Mix Propagation Times]
count    7.000000
mean     1.122000
std      0.106276
min      1.009000
25%      1.024500
50%      1.157000
75%      1.174500
max      1.290000
dtype: float64

[Broadcast Dissemination Times]
count    7.000000
mean     0.118429
std      0.004353
min      0.111000
25%      0.116000
50%      0.120000
75%      0.121500
max      0.123000
dtype: float64

==========================================
Message Size Distribution
==========================================
   msg_size   count
0      1405  179982

==========================================
Node States of All Nodes over Time
SENDING:-1, IDLE:0, RECEIVING:1
==========================================
        Node-0  Node-1  Node-2  Node-3  Node-4  Node-5
0            0       0       0       0       0       0
1            0       0       0       0       0       0
2            0       0       0       0       0       0
3            0       0       0       0       0       0
4            0       0       0       0       0       0
...        ...     ...     ...     ...     ...     ...
999995       0       0       0       0       0       0
999996       0       0       0       0       0       1
999997       0       0       0       0       0       0
999998       0       0       0       1       0       0
999999       0       0       0       0       0       0

[1000000 rows x 6 columns]

Saved DataFrame to all_node_states_2024-07-23T09:10:59.csv

State Counts per Node:
    Node-0  Node-1  Node-2  Node-3  Node-4  Node-5
 0  960004  960004  960004  960004  960004  960004
 1   29997   29997   29997   29997   29997   29997
-1    9999    9999    9999    9999    9999    9999

Simulation complete!

Please note that the result of node state analysis is saved as a CSV file, as printed in the console.

If you run the simulation again with the different parameters and want to compare the results of two simulations, you can calculate the hamming distance between them:

python -m cmd.hamming \
    all_node_states_2024-07-15T18:20:23.csv \
    all_node_states_2024-07-15T19:32:45.csv

The output is a floating point number between 0 and 1. If the output is 0, the results of two simulations are identical. The closer the result is to 1, the more the two results differ from each other.

Hamming distance: 0.29997