Convergence analysis of genetic algorithms for topology control in MANETs
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 distrib...
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| creator | Sahin, Cem Safak Gundry, Stephen Urrea, Elkin Uyar, M Umit Conner, Michael Bertoli, Giorgio Pizzo, Christian |
| description | 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. |
| doi_str_mv | 10.1109/SARNOF.2010.5469783 |
| format | Conference Proceeding |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Algorithm design and analysis bio-inspired algorithms Convergence Genetic algorithms Machine learning algorithms MANETs Markov chains Mobile ad hoc networks Mobile communication Routing Software agents Stochastic processes Topology topology control |
| title | Convergence analysis of genetic algorithms for topology control in MANETs |
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