A Wireless Sensor Network simulator in Python and C++ (via SWIG).

It basically simulates the communication among nodes and communication with the base station. It has a energy model that helps estimates the network lifetime. It has some pre-defined scenarios (including clustering techniques):

• Direct Communication (from nodes directly to the base station);
• MTE
• LEACH
• FCM

It also implements a modified version of PSO (Particle Swarm Optimization) in order to schedule sleeping slots to every node at every communication round. This implementation is based on this paper, but contains improvements, specially concerning the learning of better solutions. NSGA-II is also implemented.

1. Choose your settings in the configuration file (config.py)

2. Compile C++/Python wrappers: python setup.py build_ext --inplace

3. python run.py

All non-trivial requirements (the ones you cannot get via pip install) are inside this repository.

1. M. Ettus. System Capacity, Latency, and Power Consumption in Multihop-routed SS-CDMA Wireless Networks. In Radio and Wireless Conference (RAWCON 98), pages 55–58, Aug. 1998

2. W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, Energy-efficient communication protocols for wireless sensor networks, In Proceedings of the 33rd Annual Hawaii International Conference on System Sciences (HICSS), Hawaii, USA, January 2000.

3. D. C. Hoang, R. Kumar and S. K. Panda, "Fuzzy C-Means clustering protocol for Wireless Sensor Networks," 2010 IEEE International Symposium on Industrial Electronics, Bari, 2010, pp. 3477-3482.

4. C. Yu, W. Guo and G. Chen, "Energy-balanced Sleep Scheduling Based on Particle Swarm Optimization in Wireless Sensor Network," 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum, Shanghai, 2012, pp. 1249-1255.

5. K. Deb, A. Pratap, S. Agarwal and T. Meyarivan, "A fast and elitist multiobjective genetic algorithm: NSGA-II," in IEEE Transactions on Evolutionary Computation, vol. 6, no. 2, pp. 182-197, April 2002.