The ns-3 Simulation Execution Manager

Efficiently perform multiple ns-3 simulations and export the results for processing in two shell commands:

sem run
sem export output.mat

Alternatively, achieve finer control and go from simulation running to plotting results in a few lines of Python code:

# Create a simulation campaign
>>> import sem
>>> campaign ='examples/ns-3',
...   'wifi-multi-tos', '/tmp/results')

# Run desired simulations with various parameter combinations
>>> campaign.run_missing_simulations(
...   {'nWifi': 1, 'distance': 1, 'simulationTime': 10,
...   'useRts': ['false', 'true'], 'mcs': [1, 3, 5, 7],
...   'channelWidth': 20, 'useShortGuardInterval': 'false'},
...   runs=3)

Running simulations: 100% 24/24 [00:42<00:00,  1.77s/simulation]

# Access results (stdout, stderr and generated files)
>>> results = campaign.db.get_complete_results()

Feature highlights

  • Supports Python 3.5+;
  • Runs multiple simulations in parallel;
  • Automatically leverages DRMAA-compatible computing clusters when available;
  • Can parse results into Pandas dataframe, Xarray dataarray and Numpy ndarray. Save results in MATLAB .mat, Numpy .npy and directory tree formats;
  • Enforces simulation reproducibility by requiring git-based codebase tracking.