Cuttlefish Optimization based Clustering Approach (COCA) to improve the Quality of Service (QoS) for Flying Ad-Hoc Network (FANET)

Drones are widely utilized for several real time applications like rescue, military, medical and disaster applications in flying ad-hoc networks (FANETs). Small flying time and inappropriate routing mechanism are serious problems which are arises due to restricted battery capacity and very high mobility in drones. We proposed a Cuttlefish Optimization based Clustering Approach (COCA) to reduce the key issues of drones in FANET. Clustering is performed by utilizing Cuttlefish optimization and outcomes of experiments illustrate the higher efficiency of COCA in terms of PDR (packet delivery ratio), cluster existence time, end to end delay and energy expenditure against other optimization scheme CLPSO, CAVDO and ECRNET.