Dynamic Leader Selection in a Master-Slave Architecture-Based Micro UAV Swarm

In this paper, we present a method for dynamically selecting leaders in a master-slave communication model in a swarm of micro-Unmanned Aerial Vehicles (UAVs). With the growing size of the UAV swarm in complex missions, it becomes a challenge to control them for efficient execution of missions. In a traditional centralized communication model where all UAVs in the swarm are controlled directly through ground control, channel capacity limits the number of UAVs in the swarm which restricts the scalability. In the context of low-power miniature drones, we limit the communication of the ground Base Station (gBS) with only one UAV (leader) which controls the rest of the UAVs (followers). Towards this, we propose a greedy heuristic method for selecting the UAV leader that requires minimal time to communicate with the gBS in real-time. The proposed master-slave model enhances the scalability of the swarm by improving the utilization of channel resources. Simulation results demonstrate that the proposed dynamic leader selection enhances the lifetime of the entire network with a multifold decrease in energy consumption, compared to the state-of-the-art. Additionally, the lifetime of the network also decreases on operating with a single UAV leader. We also observe reductions in delays by almost 60% and an increase in data rate by 50%.