Abstract
With the rapid growth of application demands and the real-time change of environmental situations, the defects of the UAV task network in adaptability, flexibility, and resilience are becoming more and more prominent. The current network architecture that the junction of points and lines is fixed cannot dynamically provide capacity requirements in real-time due to the failure nodes encountered in the Unmanned Aerial Vehicle (UAV) task scheduling process. To address this challenging issue, this paper proposes a flexible network architecture supporting dynamic fault-tolerant task scheduling model (DSM-FNA) for the UAV cluster. To be specific this paper resorts to super network theory, combining the management theory of flexible network and resilience network to carry out the organizational calculation on the model, and also draw upon linear transformation function to weight and stratify the capability value according to the ability requirement required by the task. Then, a flexible network architecture dynamic scheduling algorithm (FDSA) is proposed, and the substitution strategy is designed for the failure point, to realize the capability and dynamically adapt to the task. Finally, compared with the classical Max-Min algorithm and other algorithms, it is verified that the FDSA algorithm performs better dynamic adjustment for quick response in case of UAV cluster emergencies.
Highlights
The rapid development of economic information globalization, the deepening of the concept of unmanned intelligent operation, the rapid progress of AI / ML technology, the application of unmanned platforms in various fields of land, sea, and air, and the adaptive task architecture of Unmanned Aerial Vehicle (UAV) clusters has become a research hotspot
To implement the scheduling model we proposed, and compare it with several traditional algorithms, the simulation experiment proves that our research is intentional, and it can be used for the follow-up work of the dynamic scheduling of the UAV cluster architecture
This paper presents the dynamic scheduling algorithm flow and its pseudo-code of the UAV task architecture network based on the flexible network architecture, which is automatically started when confronted with the emergent situation
Summary
The rapid development of economic information globalization, the deepening of the concept of unmanned intelligent operation, the rapid progress of AI / ML technology, the application of unmanned platforms in various fields of land, sea, and air, and the adaptive task architecture of Unmanned Aerial Vehicle (UAV) clusters has become a research hotspot. T. Duan et al.: Dynamic Tasks Scheduling Model of UAV Cluster Based on Flexible Network Architecture. The integration of the dynamic scheduling model of flexible network architecture (DSM-FNA) into existing combat systems will be the main form of future combat battlefield and play a pivotal role in the development of DSMFNA capabilities. To implement the scheduling model we proposed, and compare it with several traditional algorithms, the simulation experiment proves that our research is intentional, and it can be used for the follow-up work of the dynamic scheduling of the UAV cluster architecture. A flexible dynamic scheduling algorithm (FDSA) for network architecture is designed and compared with the classical Max-Min algorithm and other algorithms. The sixth part is the research summary of this paper
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