论文标题

具有多余依赖性的单层网络的鲁棒性增强

Enhanced robustness of single-layer networks with redundant dependencies

论文作者

Timár, Gábor, Kovács, György, Mendes, José Fernando F.

论文摘要

单层网络中的依赖关系链接提供了一种在网络系统中建模非本地渗透效应的方便方法,在某些对节点对只能共同运行的网络系统中。我们研究了该模型弱变体的渗透特性:如果至少一个依赖性邻居处于活动状态,则具有依赖性邻居的节点可能会继续起作用。我们表明,依赖性规则的这种放松允许更健壮的结构和丰富的批判现象,因为渗透不是由有限的依赖簇严格决定的。我们研究了Erdös-rényi和随机无标度网络,并具有基本的Erdös-rényi依赖性链接网络。我们确定了一个特殊的“尖”点,在该点以上系统始终是稳定的,而与依赖关系的密度无关。我们发现连续且不连续的杂种渗透转变,由Erdös-Rényi网络的三个智力点隔开。对于具有有限度截止的无标度网络,我们观察到临界点的出现,并在一定程度分布指数的一定范围内进行相应的双重转变。我们表明,在临界点出现的参数空间中的一个特殊点上,巨大的可行群集具有不寻常的关键奇异性$ s-s_c \ propto(p-p_c)^{1/4} $。我们研究网络的鲁棒性,其中连通性程度和依赖关系的相关性相关,并发现无标度网络能够保留​​其高弹性,以实现足够强的正相关性,即,当集线器受到更大的冗余性保护时。

Dependency links in single-layer networks offer a convenient way of modeling nonlocal percolation effects in networked systems where certain pairs of nodes are only able to function together. We study the percolation properties of the weak variant of this model: nodes with dependency neighbours may continue to function if at least one of their dependency neighbours is active. We show that this relaxation of the dependency rule allows for more robust structures and a rich variety of critical phenomena, as percolation is not determined strictly by finite dependency clusters. We study Erdös-Rényi and random scale-free networks with an underlying Erdös-Rényi network of dependency links. We identify a special "cusp" point above which the system is always stable, irrespective of the density of dependency links. We find continuous and discontinuous hybrid percolation transitions, separated by a tricritical point for Erdös-Rényi networks. For scale-free networks with a finite degree cutoff we observe the appearance of a critical point and corresponding double transitions in a certain range of the degree distribution exponent. We show that at a special point in the parameter space, where the critical point emerges, the giant viable cluster has the unusual critical singularity $S-S_c \propto (p-p_c)^{1/4}$. We study the robustness of networks where connectivity degrees and dependency degrees are correlated and find that scale-free networks are able to retain their high resilience for strong enough positive correlation, i.e., when hubs are protected by greater redundancy.

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