eda-ricercatore / NetSim

An optimization tool for telecommunication networks. It is optimized via a multi-objective evolutionary algorithm, so that the trade-off between pleiotropy and redundancy can be explored.

NetSim

Summary

An optimization tool for telecommunication networks. It is optimized via a multi-objective evolutionary algorithm, so that the trade-off between pleiotropy and redundancy can be explored.

Not-so-Terse Description

It is primarily developed in Java, and has MATLAB scripts to process the experimental data for statistical analysis.

It also uses a Makefile (you can also use the UNIX shell script) to set up and run this program.

Its software architecture is organized into the following directories:

1. utility: common functions that are used for different modules in the software;
2. gui: the Graphical User Interface (GUI) for the software;
3. tests: experimental test results;
4. scripts: scripts for processing the experimental data in MATLAB;
5. results: experimental test results;
6. population: implementation of the graph data structure in the "graph" subdirectory and some graph algorithms used to determine certain properties of the telecommunication networks;
7. ecomp: implementation of the multi-objective evolutionary algorithm

There are also other files, such as the README.md file (i.e., this file). Where possible, unit test and module tests are provided in each software module/subdirectory.

WARNING

This is the latest recent build that I can access. I was trying to modify the multi-objective evolutionary algorithm to seek Pareto optimal trade-offs in an attempt to meet a conference call for papers deadline. Unfortunately, I ended up mutilating the code, and have not worked on project since. Use the makefile to compile and run the project; that is, run: make all. To determine the number of lines of code, including comments, that my teammate and I have written, try: make klocs.

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Details, where are the details???

Details about this work.

Conference paper describing this work.

A research paper describing this work is available as a conference paper, which is referenced as follows.

Z. Ong, A. H.-W. Lo, M. Berryman, and D. Abbott, "Multi-objective evolutionary algorithm for investigating the trade-off between pleiotropy and redundancy," in Proceedings of SPIE Complex Systems, vol. 6039, Brisbane, Australia, pp. 237-248, 11-14 December, 2005. DOI

Further details about this work.

Further details of a thesis describing this work, including a set of presentation slides for the thesis defense and the research proposal are available.

DOI to access source code of the repository