A Node Importance Ranking Method Based on the Rate of Network Entropy Changes

When a network is suffering from attack and cannot afford to protect all the nodes, it is reasonable to pick up the important nodes and then protect them with priorities. Many node importance ranking methods have been proposed, but most of them are only based on static network topology analysis and rarely take the impact of dynamic network traffic into account. As a result, we devise a novel method named MixR (Mix Ranking) algorithm which takes both network topology and dynamic network load into account to rank the nodes importance. To show the effectiveness of MixR algorithm, we apply SIR (Susceptible-Infected-Recovered) as an inference model to compare our proposed method with the other known node importance ranking methods such as Degree Centrality(DC), Closeness Centrality(CC), Eigenvalue Centrality(EC) and Semi-local Centrality. The experimental results show that MixR algorithm outperforms those known methods with respect to dynamic network traffic changes in the network.