Performance of distributed clustering with weighted optimization algorithm for MANET Cognitive Radio

Mobile Ad-Hoc networks (MANET) are widely used for data communication between mobile nodes on the digital battlefield. Clustering has evolved as an important research topic in military MANETs in reference to supporting the ability of C4I system reconfiguration in highly dynamic operation. Clustering is a process that divides the network nodes into groups according to the command system. Each cluster has a Cluster Head (CH) as a coordinator within the cluster. For policy-based MANET Cognitive Radio (CR) it is very important to have an appropriate set of policies according to the variety of specific scenarios of the data network usage. A few algorithms have been recently studied and proposed for distributed clustering. The presented algorithm is based on the multi-criteria decision using the weighted function of the main network parameters. An appropriate selection of weights values for each particular scenario is critical for the effectiveness of MANET-CR. As the simulations have shown, the number of clusters within the network and the number of nodes in the clusters determine the ability of CR adaptation according to better usage of the available spectrum resources. The performances of the proposed algorithm has been evaluated through the simulations using OMNeT++ simulator and the results are encouraging.