The following figure explains the difference between offline and online machine learning with NetSim
C-based ML algorithms
- ML Model in C. NetSim code is in C
- Tight integration is possible since they can be compiled together
- Difficult. Low-level memory management
MATLAB/Python ML algorithms
- Inter-process communication via sockets
- Easy and user-friendly. Use inbuilt ML algorithms/APIs
Useful resources
- https://support.tetcos.com/a/solutions/articles/14000138368 - Example of reinforcement learning with NetSim (MDP, Q learning)
- Presentation explaining MATLAB-based optimization for best BS placement in 5G (PDF, 278 KB)
Example papers that have used RL with NetSim
- https://www.researchgate.net/publication/362660343_Q-Learning_Relay_Placement_for_Alert_Message_Dissemination_in_Vehicular_Networks
- https://www.researchgate.net/publication/360724660_Adaptive_Hybrid_Heterogeneous_IDS_for_6LoWPAN
- https://www.researchgate.net/publication/354845095_Reinforcement-Learning-Based_IDS_for_6LoWPAN
- https://www.researchgate.net/publication/352310525_DETONAR_Detection_of_Routing_Attacks_in_RPL-Based_IoT