Convergence analysis of genetic algorithms for topology control in MANETs
Cem Şahin, Stephen Gundry, Elkin Urrea, M. Ümit Uyar, Michael D. Conner, Giorgio Bertoli, Christian Pizzo · 2010
We describe and verify convergence properties of our forced-based genetic algorithm (FGA) as a decentralized topology control mechanism distributed among software agents. FGA uses local information to guide autonomous mobile nodes over an unknown geographical terrain to obtain a uniform node distribution. Analyzing the convergence characteristics of FGA is difficult due to the stochastic nature of GA-based algorithms. Ergodic homogeneous Markov chains are used to describe the convergence characteristics of our FGA. In addition, simulation experiments verify the convergence of our GA-based algorithm.