A Bio-Inspired Leader-based Energy Management System for Drone Fleets

TL;DR

This paper proposes a bio-inspired leader-based energy management system for drone fleets that enhances energy efficiency and extends operational time by optimizing communication roles within the network.

Contribution

It introduces a novel bio-inspired algorithm that dynamically designates a drone as a leader to improve energy conservation and communication efficiency in drone networks.

Findings

Significantly increases network efficiency

Extends drone fleet operational time

Reduces unnecessary energy consumption

Abstract

Drones are embedded systems (ES) used across a wide range of fields, from photography to shipments and even during crisis management for searching, rescuing and damage assessment activities. However, their limited battery life and high energy consumption are very important challenges, especially in networked systems where multiple drones must communicate with a Ground Base Station (GBS). This study addresses these limitations by proposing the implementation of a bio-inspired leader-based energy management system for drone fleets. Inspired by bio-behavioral models, the algorithm dynamically chooses a single drone as a Leader in a cluster to handle long-range communication with the GBS, allowing other drones to preserve their energy. The effectiveness of the proposed bio-inspired algorithm is evaluated by varying network sizes and configurations. The results demonstrate that our approach significantly increases network efficiency and service time by removing useless energy consumption communications.