Hscs: Hybridization of Self-Organized Clustering Scheme for Flying Ad-Hoc Network

Flying ad-hoc network (FANET) is a collection of unnamed aerial vehicles that communicate without any predefined infrastructure. It having dynamic topology because it is based on MANETs and also changes their frequency in a different state. Changing the state or forminga new cluster will be a challenging task. We design a new clustering mechanism in FANET using K-means Algorithm. In this technique cluster management and cluster head election will be based on SOCS with the K-means algorithm. In FANET, routing is challenging when Quality of Services (QoS) parameters need to be classified. We also propose a novel optimization technique for routing using the Firefly Algorithm (FFA) with Artificial Neural Network. Simulation analysis showed improved performance in favor of cluster construction phase, cluster lifetime, energy usage, and the probability of success as compared with ACO, GSO & SOCS.