AN APPLICATION OF HESITANT FUZZY SETS TO ELECT AN EFFICIENT CLUSTER HEAD IN AD HOC NETWORKS

Due to the important role of ad hoc networks and in particular mobile ad hoc networks (MANETs) and vehicular ad hoc networks (VANETs), in many areas, we consider the cluster head election problem for this type of network. Clustering is an efficient method to organize nodes for data transmissions and security achievement. Electing a suitable cluster head for each cluster leads to energy saving and enhancing network performance. In this study, we introduce a novel cluster head election method to be applied to both hierarchical routing protocol and hierarchical intrusion detection systems in ad hoc networks. To deal with the existing hesitation of a node to choose a cluster head, we utilize hesitant fuzzy set. We model the cluster head election problem in ad hoc network by a multi attribute hesitant fuzzy decision making problem. The attributes are determined based on the role of cluster head in the network. So we could consider the conflicting attributes. Therefore this cluster head election is more comprehensive and flexible than the existing methods