Hazard tolerance of spatially distributed complex networks
Hazard tolerance of spatially distributed complex networks
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DOI：
10.1016/j.ress.2016.08.010
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
S. Dunn;S. Wilkinson
中科院分区：
文献类型：
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作者：
S. Dunn;S. Wilkinson
在本文中，我们提出了一种新的方法来量化复杂系统的可靠性，使用网络图论的技术。近年来，网络理论已被应用于许多研究领域，并使我们能够深入了解真实的系统的行为，否则很难或不可能分析，例如日益复杂的基础设施系统。虽然这项工作在理解复杂系统方面取得了很大的进展，但绝大多数这些研究只考虑系统的拓扑可靠性，而在很大程度上忽略了其空间分量。事实表明，忽略这一空间组成部分可能会产生潜在的破坏性后果。在本文中，我们提出了一些算法，用于生成一系列具有不同拓扑和空间特征的合成空间网络，并识别具有相同特征的真实网络。我们评估节点的位置和高度连接的节点的空间分布对风险容忍度的影响，通过比较我们的通用网络的基准网络。我们讨论了这些研究结果的相关性真实的世界网络，并表明，拓扑和空间配置的组合，使许多真实的世界网络容易受到某些空间危害。
In this paper, we present a new methodology for quantifying the reliability of complex systems, using techniques from network graph theory. In recent years, network theory has been applied to many areas of research and has allowed us to gain insight into the behaviour of real systems that would otherwise be difficult or impossible to analyse, for example increasingly complex infrastructure systems. Although this work has made great advances in understanding complex systems, the vast majority of these studies only consider a systems topological reliability and largely ignore their spatial component. It has been shown that the omission of this spatial component can have potentially devastating consequences. In this paper, we propose a number of algorithms for generating a range of synthetic spatial networks with different topological and spatial characteristics and identify real-world networks that share the same characteristics. We assess the influence of nodal location and the spatial distribution of highly connected nodes on hazard tolerance by comparing our generic networks to benchmark networks. We discuss the relevance of these findings for real world networks and show that the combination of topological and spatial configurations renders many real world networks vulnerable to certain spatial hazards.