A construction algorithm of cognitive radio network with multiobjective genetic algorithm

Cognitive Radio Network Technology brings a novel approach to share the open spectrum flexibly and efficiently. However, how to further improve the network construction for reducing the redundant information has become the hot topic. Minimum Independent Dominating Set (MIDS) in graphs is a classic problem in operations research with important application in network construction design. The single objective MIDS (SMIDS) problem can be solved efficiently, but the degree constrained and multi-objective versions are NP-hard. In this paper, according to the characteristics of cognitive radio network nods, an improved Genetic Algorithm (GA) with special crossover and mutation operators is proposed to solve the problem. Experimental results showed that the proposed method for searching multi-objective MIDS (MMIDS) with improved GA outperforms the conventional methods with heuristic algorithm search in multi-objective optimization problem. And it was therefore effectively able to select the clusters for different network simulation scenarios.