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 = sem.CampaignManager.new('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.