基于鲁棒性和可控子空间的复杂网络中心性

A. Mahmood, Umair Usman, Lin Wang
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引用次数: 0

摘要

复杂的网络无处不在,其中包括航空网络、道路网络、电网网络和蛋白质到蛋白质的网络。这些网络在故障或受到攻击时具有鲁棒性,但仍需要深入研究。研究人员提出了各种技术来发现和增强网络的鲁棒性。然而,这方面还需要进一步的研究。本文研究了随机去边条件下可控子空间的鲁棒性,并给出了一个节点和一组节点上可控子空间的鲁棒性指标。本文提出了一种新的中心性CSR(可控子空间和鲁棒性)方法,基于可控子空间的最优值和可控子空间的鲁棒性对网络的重要节点进行排序。讨论了精确鲁棒性指标和近似鲁棒性指标对计算时间和精度的影响。我们用不同的中心性度量和CSR对各种真实网络的前10%重要节点进行了分析,以比较结果。通过在真实网络上的广泛实验,CSR优于其他中心性度量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CSR: A Centrality Based on Robustness and Controllable Subspace of Complex Networks
Complex networks are everywhere, some of them are airline network, road network, power grid network and protein-to-protein network. These networks are robust in failure or under attack but still needs in-depth study. Researchers have proposed various techniques to find and enhance the robustness of networks. However, furthers study required in this area. In this paper, we study the robustness of controllable subspace under random removal of edges and propose the robustness index for controllable subspace from one node as well as from a set of nodes. This work proposes a new centrality CSR (Controllable Subspace and robustness) to rank the important nodes of network based on optimal values of controllable subspace and robustness of controllable subspace. We also discuss the effects of exact robustness index and approximate robustness index on two factor: computational time, and accuracy. We show the analysis of top ten percent important nodes of various real networks with different centrality measures and CSR to compare the results. With the extensive experimentation on the real networks, CSR outperformed other centrality measures.
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