灰色信息下复杂负载网络的鲁棒性研究

Research on robustness of complex load-networks with grey information

针对复杂负载网络遭遇攻击引发的相继故障问题,考虑攻击信息的不完全准确性,建立了一个基于灰色信息的相继故障模型。灰色信息的准确度可以通过参数调节控制,随机攻击和蓄意攻击是该模型的两个特例。探讨了灰色信息下,无标度网络和随机网络遭遇边攻击而引发的节点过载故障的级联现象,对比了灰色信息对两类网络鲁棒性的影响。仿真结果表明,信息准确度的降低能明显增强无标度网络的鲁棒性,但对随机网络的影响并不明显。此外,信息准确度对网络鲁棒性的影响存在临界现象。这些结论为相继故障的防御、网络结构的设计以及现实网络的有效保护提供了理论依据。

Aiming at cascading failures in complex load-networks subject to attacks, and considering that the attack information may be incompletely precise, a cascading failures model based on grey information is proposed. The accuracy of grey information can be controlled by a tunable parameter, the random and intentional attack are two extreme cases of this model. Cascades of node overload failures triggered by edge attacks in scale-free and random networks are investigated, and the effects of grey information on the robustness of two types of networks are compared. The simulation results show that decreasing the precision of information can remarkably enhance the robustness of scale-free networks; however, in random networks the situation is not obvious. Furthermore, the critical phenomenon that information accuracy affects networks robustness is observed. These provide academic basis to defense 0f cascading, failures, design of network architecture and effective protection of real networks.