Fu Chenbo, Wang Xingang
Institute for Fusion Theory and Simulation, Zhejiang University, Hangzhou 310027, China.
Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Jun;83(6 Pt 2):066101. doi: 10.1103/PhysRevE.83.066101. Epub 2011 Jun 2.
While it is well recognized that realistic networks are typically growing with time, the dynamical features of their growing processes remain to be explored. In the present paper, incorporating the requirement of synchronization stability into the conventional models of network growth, we will investigate how the growing process of a complex network is influenced by, and also will influence, the network collective dynamics. Our study shows that, constrained by the synchronization stability, the network will be growing in a selective and dynamical fashion. In particular, we find that the chance for a new node to be accepted by the growing network could have a large variation, i.e., it follows roughly a power-law distribution. Furthermore, we find that, with the dynamical growth, the network is always developed into structures of clear scale-free features, despite the form of the link attachment (preferential or random). The dynamical properties of network growth are studied using the method of eigenvalue analysis, and they are verified by direct simulations of coupled chaotic oscillators. Our study implies that, driven by the network collective dynamics, network growth could also be highly dynamical.
虽然人们普遍认识到现实网络通常会随着时间增长,但其增长过程的动态特征仍有待探索。在本文中,将同步稳定性的要求纳入传统的网络增长模型,我们将研究复杂网络的增长过程如何受到网络集体动力学的影响,以及又如何影响网络集体动力学。我们的研究表明,受同步稳定性的约束,网络将以一种选择性和动态的方式增长。特别地,我们发现新节点被增长网络接受的机会可能有很大差异,即大致遵循幂律分布。此外,我们发现,随着动态增长,无论链路附着形式(优先或随机)如何,网络总是发展成具有明显无标度特征的结构。使用特征值分析方法研究了网络增长的动态特性,并通过耦合混沌振荡器的直接模拟进行了验证。我们的研究表明,在网络集体动力学的驱动下,网络增长也可能是高度动态的。