Performance Evaluation of WMN-GA Simulation System for Different Settings of Genetic Operators Considering Giant Component and Number of Covered Users

Admir Barolli, Makoto Takizawa, Tetsuya Oda, Evjola Spaho, Leonard Barolli, Kazunori Uchida and Fatos Xhafa
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Admir Barolli: Seikei University, Japan
Makoto Takizawa: Seikei University, Japan
Tetsuya Oda: Fukuoka Institute of Technology, Japan
Evjola Spaho: Fukuoka Institute of Technology, Japan
Leonard Barolli: Fukuoka Institute of Technology, Japan
Kazunori Uchida: Fukuoka Institute of Technology, Japan
Fatos Xhafa: Technical University of Catalonia, Spain

International Journal of Distributed Systems and Technologies (IJDST), 2012, vol. 3, issue 3, 1-14

Abstract: In this paper, the authors propose and implement a system based on Genetic Algorithms (GAs) called WMN-GA. They evaluated the performance of WMN-GA for 0.7 crossover rate and 0.3 mutation rate, exponential ranking and different distribution of clients considering size of giant component and number of covered users parameters. The simulation results show that for normal distribution the system has better performance. The authors also carried out simulations for 0.8 crossover rate and 0.2 mutation rate. The simulation results show that the setting for 0.7 crossover rate and 0.3 mutation rate offers better connectivity and user coverage.

Date: 2012
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