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Diversity of Structural Controllability of Complex Networks With Given Degree Sequence

机译:具有定度序列的复杂网络结构可控性的多样性

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We investigate to what extent the degree sequence of a directed network constrains the number of driver nodes. We develop a pair of algorithms that take a directed degree sequence as input and aim to output a network with the maximum or minimum number of driver nodes. We find an upper bound for the maximum and a lower bound for the minimum, and show that the algorithms achieve these bounds for all real and model networks, with few exceptions characterized by tiny system size and heterogeneous degree distributions. Applying these algorithms to a broad range of real networks, we show the gap between the upper and lower bounds can vary dramatically across different degree sequences. Thus, we introduce the notion of structural control complexity to capture how much more difficult it is to control a specific network beyond what is required given its degree sequence, suggesting additional structure is present. Using model networks, we numerically and analytically investigate how typical features of the degree distribution affect the range of required driver nodes. We find that the minimum is determined by the number of sources or sinks, while the maximum is strongly affected by the presence of hubs.
机译:我们调查定向网络的程度序列在多大程度上限制了驱动程序节点的数量。我们开发了一对算法,该算法将定向度序列作为输入,并旨在输出具有最大或最小驱动器节点数量的网络。我们发现最大值和下限的最小界限,并表明该算法实现了所有真实和型号网络的这些界限,这些界限少数例外的例外,以微小的系统尺寸和异构度分布为特征。将这些算法应用于广泛的真实网络,我们在不同程度序列中显示了上下边界之间的间隙可以急剧变化。因此,我们介绍了结构控制复杂性的概念,以捕获控制特定网络超出给定度序列所需的特定网络的困难程度的概念,建议存在额外的结构。使用模型网络,我们在数值上和分析研究了程度分布的典型特征如何影响所需的驱动程序节点的范围。我们发现最小值由源代码或汇位的数量决定,而最大值受集线器的存在强烈影响。

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