Podobnik B, Majdandzic A, Curme C, Qiao Z, Zhou W-X, Stanley H E, Li B
Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts 02215, USA and Faculty of Civil Engineering, University of Rijeka, 51000 Rijeka, Croatia and Zagreb School of Economics and Management, 10000 Zagreb, Croatia and Faculty of Economics, University of Ljubljana, 1000 Ljubljana, Slovenia.
Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts 02215, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2014 Apr;89(4):042807. doi: 10.1103/PhysRevE.89.042807. Epub 2014 Apr 15.
To model volatile real-world network behavior, we analyze a phase-flipping dynamical scale-free network in which nodes and links fail and recover. We investigate how stochasticity in a parameter governing the recovery process affects phase-flipping dynamics, and we find the probability that no more than q% of nodes and links fail. We derive higher moments of the fractions of active nodes and active links, fn(t) and fℓ(t), and we define two estimators to quantify the level of risk in a network. We find hysteresis in the correlations of fn(t) due to failures at the node level, and we derive conditional probabilities for phase-flipping in networks. We apply our model to economic and traffic networks.
为了对动态变化的现实世界网络行为进行建模，我们分析了一个节点和链路会发生故障并恢复的相位翻转动态无标度网络。我们研究了控制恢复过程的参数中的随机性如何影响相位翻转动态，并且我们发现不超过q%的节点和链路发生故障的概率。我们推导了活跃节点和活跃链路比例fn(t)和fℓ(t)的高阶矩，并且我们定义了两个估计量来量化网络中的风险水平。我们发现由于节点层面的故障，fn(t)的相关性中存在滞后现象，并且我们推导了网络中相位翻转的条件概率。我们将我们的模型应用于经济网络和交通网络。
