优化饱和信息负载分析,增强无人机群系统的鲁棒性

IF 5 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Jian Wu, Yichuan Jiang, Junjun Tang, Linfei Ding
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引用次数: 0

摘要

饱和信息负载是指蜂群网络中无人机(UAV)节点接收的信息达到其处理能力的过载极限。当无人机蜂群在不确定、对抗性强的复杂环境中执行任务时,无人机的过载会导致信息分流,可能导致其他无人机也出现过载和分流,影响整个蜂群网络的传输效率和鲁棒性,进而影响蜂群执行任务的信息感知能力、执行能力和协调能力。因此,本文提出了一种基于饱和信息负载的无人机蜂群网络拓扑建模方法,在网络模型中设定节点的饱和信息负载,以合理分配网络资源,优化网络拓扑结构。此外,通过对复杂网络的鲁棒性实验和不同饱和信息负载与三种典型建模方法的对比分析,基于饱和信息负载的网络结构建模方法在网络连通性、网络通信效率和抗毁性等方面具有突出的优势和性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Optimal saturated information load analysis for enhancing robustness in unmanned swarms system

Optimal saturated information load analysis for enhancing robustness in unmanned swarms system

Saturated information load is defined as the information received by a unmanned aerial vehicle (UAV) node in a swarm network reaches the overload limit of its processing capability. When a UAV swarm performs a mission in an uncertain and adversarial complex environment, overloading of UAVs will lead to information diversion, which may cause other UAVs to experience overloading and diversion as well, affecting the transmission efficiency and robustness of the entire swarm network, which in turn affects the information sensing ability, execution ability, and coordination ability of the swarm in performing the mission. Therefore, this paper proposes a saturated information load-based UAV swarm network topology modelling method, which sets the saturated information load of the nodes in the network model in order to reasonably allocate network resources and optimise the network topology. In addition, through robustness experiments of complex networks and comparative analysis of different saturated information loads and three typical modelling methods, the saturated information load-based network structure modelling method has outstanding advantages and performance in terms of network connectivity, network communication efficiency, and destruction resistance.

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来源期刊
Complex & Intelligent Systems
Complex & Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
9.60
自引率
10.30%
发文量
297
期刊介绍: Complex & Intelligent Systems aims to provide a forum for presenting and discussing novel approaches, tools and techniques meant for attaining a cross-fertilization between the broad fields of complex systems, computational simulation, and intelligent analytics and visualization. The transdisciplinary research that the journal focuses on will expand the boundaries of our understanding by investigating the principles and processes that underlie many of the most profound problems facing society today.
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