Cascading failures always occur in computer networks in which network traffic is severely impaired or halted to or between larger sections of the network, caused by failing or disconnected hardware or software. "Load-capacity" models are usually used for solving network traffic problems and exploring the mechanisms of cascading failures. Centering on cascading failures in complex networks, the following work is done. Firstly, the effect of network traffic load on cascading failures is analyzed. It indicates that the communication activity among network nodes presents a self-organized criticality phenomenon, and the influence on the network robustness brought by the traffic change of those original inactive nodes is much greater than that brought by those active ones. Secondly, under the constraints of economy and technology, a cost factor is introduced to model the relationship of network capacity and load, so as to reveal their constraints relationship. Finally, Centering on the issue of "how to allocate the limited redundant resources to a network with specific structure in order to improve its robustness", an evolutionary algorithm to search an optimized capacity-allocation strategy is proposed, which makes the network achieve optimal robustness with the same resources. Experiments show that our algorithm can find a better result of capacity-allocation than the ones with linear or preferences-attached strategies.%网络相继故障是网络脆弱性研究中的热点问题.采用负荷-容量模型对复杂网络的相继故障进行建模分析.首先分析了网络流量负荷的突发模式对相继故障的影响.实证研究发现,网络实体间的通信活跃性具有自组织临界性.在网络安全地应急响应时,应该更关注那些原本不活跃的结点间流量的变化；其次,引入成本因子对经济、技术条件制约下的网络资源受限生成过程及网络容量-负荷关系建模,以揭示网络结点的容量-负荷之间存在着怎样的制约关系；最后提出了一种基于容量相互补偿的搜索式分配算法,以获得有限资源下最优的网络鲁棒性容量分配策略.实验证明,算法能够找到比线性分配或偏好负荷的偏好依附分配策略更好的结果.
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