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

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.

F3n

“…The heuristic approaches based on Fuzzy Logic (FL) and Genetic Algorithms (GA) can prove to be efficient for traffic control in wireless networks (Chan, Sheriff, Hu Conforto & Tocci, 2001;Barolli, Koyama, Suganuma & Shiratori, 2003;Barolli, Takizawa, Oda, Spaho, Barolli, Uchida & Xhafa, 2012).…”