A Novel Load Capacity Model with a Tunable Proportion of Load Redistribution against Cascading Failures

Defence against cascading failures is of great theoretical and practical significance. A novel load capacity model with a tunable proportion is proposed. We take degree and clustering coefficient into account to redistribute the loads of broken nodes. The redistribution is local, where the loads of broken nodes are allocated to their nearest neighbours. Our model has been applied on artificial networks as well as two real networks. Simulation results show that networks get more vulnerable and sensitive to intentional attacks along with the decrease of average degree. In addition, the critical threshold from collapse to intact states is affected by the tunable parameter. We can adjust the tunable parameter to get the optimal critical threshold and make the systems more robust against cascading failures.

[1]  Réka Albert,et al.  Structural vulnerability of the North American power grid. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  Mahdi Jalili,et al.  Topology and vulnerability of the Iranian power grid , 2014 .

[3]  Rong Li-li,et al.  Cascading failures on complex networks based on the local preferential redistribution rule of the load , 2009 .

[4]  K. Goh,et al.  Universal behavior of load distribution in scale-free networks. , 2001, Physical review letters.

[5]  Huijun Sun,et al.  A robust matching model of capacity to defense cascading failure on complex networks , 2008 .

[6]  Dong-Li Duan,et al.  Dynamical robustness of networks against multi-node attacked , 2017 .

[7]  Ian Dobson,et al.  Examining criticality of blackouts in power system models with cascading events , 2002, Proceedings of the 35th Annual Hawaii International Conference on System Sciences.

[8]  Kwang-Il Goh,et al.  Packet transport and load distribution in scale-free network models , 2003 .

[9]  Jun Du,et al.  Cascading failure in interconnected weighted networks based on the state of link , 2017 .

[10]  B Kahng,et al.  Sandpile on scale-free networks. , 2003, Physical review letters.

[11]  Dong Hwan Kim,et al.  Network topology and resilience analysis of South Korean power grid , 2017 .

[12]  Ziyou Gao,et al.  Clustering and congestion effects on cascading failures of scale-free networks , 2007 .

[13]  Stephanie Forrest,et al.  Email networks and the spread of computer viruses. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  M. Barthelemy.  Betweenness centrality in large complex networks , 2003, cond-mat/0309436.

[15]  Lili Rong,et al.  A model for cascading failures in scale-free networks with a breakdown probability , 2009 .

[16]  Guanrong Chen,et al.  Universal robustness characteristic of weighted networks against cascading failure. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  Jian Xu,et al.  Cascading failures in coupled map lattices. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[18]  Keqiu Li,et al.  A Cascading Failure Model for Command and Control Networks with Hierarchy Structure , 2018, Secur. Commun. Networks.

[19]  Qiang Yang,et al.  Modeling and analysis of cascading failure in directed complex networks , 2014 .

[20]  P. Erdos,et al.  On the evolution of random graphs , 1984 .

[21]  Tao Zhou,et al.  A limited resource model of fault-tolerant capability against cascading failure of complex network , 2007, 0708.4023.

[22]  Jun Du,et al.  Invulnerability of scale-free network against critical node failures based on a renewed cascading failure model , 2015 .

[23]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[24]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[25]  Xiao-Dong Ling,et al.  Critical thresholds for scale-free networks against cascading failures , 2014 .

[26]  Duncan J Watts,et al.  A simple model of global cascades on random networks , 2002, Proceedings of the National Academy of Sciences of the United States of America.