Research on resilience model of UAV swarm based on complex network dynamics

Abstract

The resilience of UAV swarms mainly revolves around ensuring stable and uninterrupted operations. Malicious attacks can implement the adverse impacts of potential threats through swarm communication links. In this context, the SIS (Susceptible → Infected → Susceptible) method is suitable for describing the information transmission within UAV swarms. An enhanced resilience model of the UAV swarm is proposed in this study, which incorporates the factors of self-dynamics, dynamics of topology, dynamics of information transmission, and SIS into the complex network model. The model proposed in this paper has the capability to effectively capture changes in the network topology as well as the dynamics of the system. The average number of susceptible drones is utilized as the metric to evaluate the resilience of the swarm. Furthermore, an experiment is conducted where a UAV swarm successfully carries out a surveillance mission. The proposed model not only enables the support of mission planning but also facilitates the design enhancements of UAV swarms.