基于相继故障信息的网络节点重要度演化机理分析

分析了过载机制下节点重要度的演化机理.首先,在可调负载重分配级联失效模型基础上,根据节点失效后其分配范围内节点的负载振荡程度,提出了考虑级联失效局域信息的复杂网络节点重要度指标.该指标具有两个特点:一是值的大小可以清晰地指出节点的失效后果;二是可以依据网络负载分配范围、负载分配均匀性、节点容量系数及网络结构特征分析节点重要度的演化情况.然后,给出该指标的仿真算法,并推导了最近邻择优分配和全局择优分配规则下随机网络和无标度网络节点重要度的解析表达式.最后,实验验证了该指标的有效性和可行性,并深入分析了网络中节点重要度的演化机理,即非关键节点如何演化成影响网络级联失效行为的关键节点.

Evolution mechanism of node importance based on the information about cascading failures in complex networks

This paper mainly focuses on the evolution mechanism of node importance based on the information about cascading failures. Firstly, a novel node importance indicator is proposed according to the load turbulence of each node in the redistribution range based on a tunable load redistribution model. The indicator has two characteristics: one is that the failure consequence of the considered node can be clearly pointed out by its value, and the other is that the evolution mechanism of node importance can be analyzed with the factors of load redistribution rule, node capacity, and structural characteristics of the network. Then, an evaluation algorithm is presented. The indicator analytic formulas of Erdös-Rényi networks and Barabási-Albert networks are also presented respectively with the neighbor preferential and global preferential allocation rules. The experiments demonstrate the effectiveness and feasibility of the indicators and its algorithm, with which we also analyze the node importance evolution mechanism in-depth, namely how the not-so-great nodes in structure turns into the critical nodes to trigger cascading failure in complex networks.
Keywords： complex network cascading failure importance robustness