Applying genetic algorithms for multiradio wireless mesh network planning

Two main issues that are involved in the performance of multichannel multiradio wireless mesh networks (WMNs) are channel assignment (CA) and multichannel routing (MCR). The joint CA and MCR problem has been proven to be NP-hard. In this paper, we propose to apply genetic algorithms for the CA problem and tackle MCR using linear-programming techniques. Because CA and MCR tend to interact with each other, to reflect such an interplay property, we evaluate the fitness value of a chromosome (certain CA configuration) in our genetic algorithms (GAs) by computing the linear objective function. Therefore, we successfully decouple the two problems and obtain an optimized CA configuration with a corresponding MCR schedule in polynomial time at the WMN planning stage. We demonstrate the detailed genetic evolution processes for three WMNs with different deployment constraints, which serves as a useful guideline on customizing WMNs under various requirements. Simulation results show that the proposed approach effectively increases the network capacity.