Topology Control of Drones Using Bio-Inspired Intelligent Firefly-Grasshopper Algorithm for Searching Intruder Unmanned Aerial Vehicle

Abstract

In this contemporary technological age, where it is possible to enjoy the benefits of growth in daily life, at the same time, it is difficult to escape from its hidden or obvious devastation. The same goes for the Unmanned Aerial Vehicle (UAV)/Drone technology, which is creating turmoil at the universal stage. Here, the work is taken up on the coordination of UAV swarm considering the wobbling effect due to the wind advection. A Bio-inspired Intelligent Firefly-Grasshopper (BIFG) Algorithm is proposed for the cluster formation, maintenance of the topology and communication among each other. Cluster formation is based upon the UAV’s energy levels, inspired by the Firefly algorithm (FA), which is followed by the head selection to communicate with the Ground Base-station (GS). The management of the rapidly changing topology of the drones is done with the Grasshopper optimization algorithm (GOA) to avoid an inter-UAV collision. Based on the behaviour of the swarm of UAVs, a Back Propagation Neural Network (BPNN) is used to minimize the error caused due to the wobbling effect, which is one of the major causes of the deviation from the desired outcome. For communication among the cluster members, an optimal topology-based routing protocol is used to transmit the data correctly. Further, the performance of the BIFG algorithm is assessed while taking various factors into account. The application of the proposed work is to search for intruder UAVs in a restricted area, like an airport.