Performance evaluation for different settings of crossover and mutation rates considering number of covered users
Leonard Barolli, Evjola Spaho, Tetsuya Oda, Admir Barolli, Fatos Xhafa, Makoto Takizawa · 2011
Wireless Mesh Networks (WMNs) have become an important networking infrastructure for providing cost-efficient broadband wireless connectivity. In this paper, we propose and implement a system based on Genetic Algorithms (GAs) called WMN-GA. We evaluate the performance of WMN-GA for 0.7 crossover rate and 0.3 mutation rate, Exponential Ranking and different distribution of clients considering number of covered users parameters. The simulation results show that for Normal Distribution the system has better performance. We carried out also simulations for Normal Distribution and 0.8 crossover rate and 0.2 mutation rate. The simulation results shows that the setting for 0.7 crossover rate and 0.3 mutation rate offers better user coverage.