Using Imperialist Competitive Algorithms in Clustering of Wireless Mesh Networks

Load balancing can be used to extend the lifetime of a Mesh Network and thus reducing the traffic congestion and improving the network performance. Various approaches have been proposed for load balancing in WMN. This study takes a closer look at existing solutions with the application of clustering techniques to solve routing and congestion control problems because it offers scalability and enhances the availability of network and reduced overheads. The nature of the problem of clustering is NP-hard and using meta-heuristic and evolutionary algorithms can build stable and relatively efficient clusters. This paper proposes a new clustering algorithm method in WMN networks and divide the network into k clusters to manage the load in small scale and hence to reduce the overall load of WMNs. This algorithm is a centralized method and it is designed on the basis of an imperialist competitive algorithm (ICA). A WMN is divided into multiple clusters for load control and each gateway served even number of node. A cluster head estimates traffic load in its cluster. As the estimated load gets higher, the cluster head increases the routing metrics of the routes passing through the cluster. The simulation results show that the performance of the WMNs is improved with the proposed clustering method.