A Robustness Model of Complex Networks with Tunable Attack Information Parameter  

作　　者：吴俊 谭跃进 邓宏钟 李勇 

机构地区：[1]College of Information Systems and Management, National University of Defense Technology, Changsha 410073

出　　处：《Chinese Physics Letters》2007年第7期2138-2141,共4页中国物理快报（英文版）

基　　金：Supported by the National Natural Science Foundation of China under Grant No 70501032.

摘　　要：We introduce a novel model for robustness of complex with a tunable attack information parameter. The random failure and intentional attack known are the two extreme cases of our model. Based on the model, we study the robustness of complex networks under random information and preferential information, respectively. Using the generating function method, we derive the exact value of the critical removal fraction of nodes for the disintegration of networks and the size of the giant component. We show that hiding just a small fraction of nodes randomly can prevent a scale-free network from collapsing and detecting just a small fraction of nodes preferentially can destroy a scale-free network.We introduce a novel model for robustness of complex with a tunable attack information parameter. The random failure and intentional attack known are the two extreme cases of our model. Based on the model, we study the robustness of complex networks under random information and preferential information, respectively. Using the generating function method, we derive the exact value of the critical removal fraction of nodes for the disintegration of networks and the size of the giant component. We show that hiding just a small fraction of nodes randomly can prevent a scale-free network from collapsing and detecting just a small fraction of nodes preferentially can destroy a scale-free network.

关 键 词：INTENTIONAL ATTACK RANDOM GRAPHS RESILIENCE BREAKDOWN INTERNET 

分 类 号：O41[理学—理论物理]