3Dimensional improvise clustering algorithm for unmanned aerial vehicles: 3DICA

A Flying Ad-hoc Network (FANET) is a group of Unmanned Aerial Vehicles (UAVs) that operate in an ad-hoc fashion, like Mobile Ad-hoc networks (MANET) and Vehicle Ad-hoc networks (VANET). The application of UAVs has been seen broadly used in disaster management, military operations, patrolling, and environmental investigations. Data must be transferred continuously in all scenarios in Flying Ad-hoc Networks, hence connectivity between all UAVs is necessary. Because UAVs are continually in the air, their location can be estimated in 3D space. This manuscript suggests a novel cluster routing protocol 3Dimensional Improvise Clustering Algorithm (3DICA) for handling the node uncertainty problem for cluster head selection. The author calculates the energy consumption through transmission after creating the cluster head and cluster members. The simulation findings demonstrate that the suggested technique delivers more data while taking less time to construct clusters in 3 dimensions. Manuscript compares the results with other clustering routing protocols. The proposed algorithm maintains consistency and security which leads to higher cluster stability and greater energy savings.