General description: NCSim is a comprehensive simulation framework for molecular communications, utilizing flagellated bacteria for information delivery. The major focus of the framework is on different message encoding techniques. NCSim supports typical deployment policies, such as grid and random, as well as custom deployment policies. It can simulate several simultaneous links between the nanomachines. NCSim incorporates the stochastic models for bacteria mobility, and the plasmid/chromosome transfer between bacteria through the conjugation process. The tool also has an adjustable vibration generator to model different levels of stability in the environment. Currently, only the 2-dimensional configuration is supported. The accuracy of the produced metrics in major scenarios has been confirmed via comparison with analytical results in simplified scenarios.
NCSim consists of three modules: (i) physical (PHY) layer of bacterial nanonetworks, including deployment, bacteria mobility and conjugation, plus messages encoding/decoding; (ii) scenarios generator and simulation monitor; and (iii) plotting tool, intended to post-processing of raw simulation data and plots generation. The PHY module, as the most computational intensive, is implemented in C++ with a number of technical enhancements to speed up the bacteria mobility and conjugation simulations. The two latter modules are written in Python for maintenance and extension simplicity.
The user interacts with NCSim by writing small scripts on Python to define scenarios. The software also allows running any given set of scenarios in a row.
NCSim is optimised for multi-core PC and is cross-platform supporting Windows, Linux and Mac operating systems. The tool should run on a single machine with Python 2.7 or higher. Alternatively, the physical layer can be simulated in a single thread mode on almost any modern machine (only C++ compiler is required).
The simulation accuracy can also be traded for further performance improvement. First of all, the simulation of the conjugation process can be avoided that results in approximately 100 times performance increase. Also, the slot duration can be increased from 0.1s to 1s without any notable loss in the accuracy.
See also:
- S. Balasubramaniam, P. Lio’ “Multi-hop Conjugation based Bacteria Nanonetworks”, IEEE Transactions on NanoBioscience, vol. 12, no. 1, pp.47-59, March 2013.
- V. Petrov, S. Balasubramaniam, R. Lale, D. Moltchanov, P. Lio, Y. Koucheryavy, “Forward and Reverse Coding for Chromosome Transfer in Bacterial Nanonetworks,” Elsevier Journal on Nano Communications Networks, vol. 5, pp. 15–24, March–June, 2014
