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2019 | OriginalPaper | Chapter

Robustness of Network Controllability Against Cascading Failure

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Abstract

Controllability of networks widely existing in real-life systems have been a critical and attractive research subject for both network science and control systems communities. Research in network controllability has mostly focused on the effects of the network structure on its controllability, and some studies have begun to investigate the controllability robustness of complex networks. Cascading failure is common phenomenon in many infrastructure networks, which largely affect normal operation of networks, and sometimes even lead to collapse, resulting in considerable economic losses. The robustness of network controllability against the cascading failure is studied by a linear load-capacity model with a breakdown probability in this paper. The controllability of canonical model networks under different node attack strategies is investigated, random failure and malicious attack. It is shown by numerical simulations that the tolerant parameter of load-capacity model has an important role in the emergence of cascading failure, independent to the types of network. The networks with moderate average degree are more vulnerable to the cascading failure while these with high average degree are very robust. In particular, betweenness attack strategy is more harmful to the network controllability than degree attack one, especially for the scale-free networks.

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Literature
1.
go back to reference Liu, Y.Y., Slotine, J.J., Barabási, A.L.: Controllability of complex networks. Nature 473(7346), 167–173 (2011)CrossRef Liu, Y.Y., Slotine, J.J., Barabási, A.L.: Controllability of complex networks. Nature 473(7346), 167–173 (2011)CrossRef
2.
go back to reference Yuan, Z., Zhao, C., Di, Z.: Exact controllability of complex networks. Nat. Commun. 63–73 (2013) Yuan, Z., Zhao, C., Di, Z.: Exact controllability of complex networks. Nat. Commun. 63–73 (2013)
3.
go back to reference Jia, T., Pósfai, M.: Connecting core percolation and controllability of complex networks. Sci. Rep. 4, 5379 (2014) Jia, T., Pósfai, M.: Connecting core percolation and controllability of complex networks. Sci. Rep. 4, 5379 (2014)
4.
go back to reference Liu, Y.Y., Barabási, A.L.: Control principles of complex systems. Rev. Mod. Phys. 88(3), 035006 (2016)CrossRef Liu, Y.Y., Barabási, A.L.: Control principles of complex systems. Rev. Mod. Phys. 88(3), 035006 (2016)CrossRef
5.
go back to reference Menichetti, G., Dall’Asta, L., Bianconi, G.: Network controllability is determined by the density of low in-degree and out-degree nodes. Phys. Rev. Lett. 113, 078701 (2014)CrossRef Menichetti, G., Dall’Asta, L., Bianconi, G.: Network controllability is determined by the density of low in-degree and out-degree nodes. Phys. Rev. Lett. 113, 078701 (2014)CrossRef
6.
go back to reference Chen, G.R., Lou, Y., Wang, L.: A comparative robustness study on controllability of complex networks. IEEE Trans. Circ. Syst. 66(5), 828–832 (2019) Chen, G.R., Lou, Y., Wang, L.: A comparative robustness study on controllability of complex networks. IEEE Trans. Circ. Syst. 66(5), 828–832 (2019)
7.
go back to reference Lu, Z.-M., Li, X.-F.: Attack vulnerability of network controllability. PLoS ONE 11(9), e0162289 (2016)CrossRef Lu, Z.-M., Li, X.-F.: Attack vulnerability of network controllability. PLoS ONE 11(9), e0162289 (2016)CrossRef
8.
go back to reference Wang, B., Gao, L., Gao, Y., Deng, Y.: Maintain the structural controllability under malicious attacks on directed networks. EPL (Europhys. Lett.) 101, 58003 (2013)CrossRef Wang, B., Gao, L., Gao, Y., Deng, Y.: Maintain the structural controllability under malicious attacks on directed networks. EPL (Europhys. Lett.) 101, 58003 (2013)CrossRef
9.
go back to reference Xiao, Y.-D., Lao, S.-Y., Hou, L.-L., Bai, L.: Optimization of robustness of network controllability against malicious attacks. Chin. Phys. B 121(11), 678–686 (2014) Xiao, Y.-D., Lao, S.-Y., Hou, L.-L., Bai, L.: Optimization of robustness of network controllability against malicious attacks. Chin. Phys. B 121(11), 678–686 (2014)
10.
go back to reference Wang, W.-X., Ni, X., Lai, Y.-C., Grebogi, C.: Optimizing controllability of complex networks by minimum Structural perturbations. Phys. Rev. E 85, 026115 (2012)CrossRef Wang, W.-X., Ni, X., Lai, Y.-C., Grebogi, C.: Optimizing controllability of complex networks by minimum Structural perturbations. Phys. Rev. E 85, 026115 (2012)CrossRef
11.
go back to reference Hou, L.-L., Lao, S.-Y, Liu, G., Bai, L.: Controllability and Directionality in Complex Networks. Chin. Phys. Lett. 29, 108901 (2012)CrossRef Hou, L.-L., Lao, S.-Y, Liu, G., Bai, L.: Controllability and Directionality in Complex Networks. Chin. Phys. Lett. 29, 108901 (2012)CrossRef
12.
go back to reference Xiao, Y.-D., Lao, S.-Y., Hou, L.-L., Bai, L.: Edge orientation for optimizing controllability of complex networks. Phys. Rev. E 90, 042804 (2014)CrossRef Xiao, Y.-D., Lao, S.-Y., Hou, L.-L., Bai, L.: Edge orientation for optimizing controllability of complex networks. Phys. Rev. E 90, 042804 (2014)CrossRef
13.
go back to reference Liang, M., Jin, S.-Q., Wang, D.-J., Zou, X.-F.: Optimization of controllability and robustness of complex networks by edge directionality. Eur. Phys. J. B 89, 186 (2016)CrossRef Liang, M., Jin, S.-Q., Wang, D.-J., Zou, X.-F.: Optimization of controllability and robustness of complex networks by edge directionality. Eur. Phys. J. B 89, 186 (2016)CrossRef
15.
go back to reference Pu, C.-L., Pei, W.-J., Michaelson, A.: Robustness analysis of network controllability. Phys. A: Stat. Mech. Appl. 391(18), 4420–4425 (2012)CrossRef Pu, C.-L., Pei, W.-J., Michaelson, A.: Robustness analysis of network controllability. Phys. A: Stat. Mech. Appl. 391(18), 4420–4425 (2012)CrossRef
16.
go back to reference Wang, L., Fu, Y.-B., Chen, M.Z.-Q., Yang, X.-H.: Controllability robustness for scale-free networks based on nonlinear load-capacity. Neurocomputing 251, 99–105 (2017)CrossRef Wang, L., Fu, Y.-B., Chen, M.Z.-Q., Yang, X.-H.: Controllability robustness for scale-free networks based on nonlinear load-capacity. Neurocomputing 251, 99–105 (2017)CrossRef
17.
go back to reference Nie, S., Wang, X., Zhang, H., Li, Q., Wang, B.: Robustness of controllability for networks based on edge-attack. PLoS ONE 9(2), e89066 (2014)CrossRef Nie, S., Wang, X., Zhang, H., Li, Q., Wang, B.: Robustness of controllability for networks based on edge-attack. PLoS ONE 9(2), e89066 (2014)CrossRef
18.
go back to reference Sold, R.V., Rosas-Casals, M., Corominas-Murtre, B., Valverde, S.: Robustness of the European power grids under intentional attack. Phys. Rev. E 77(2), 026102 (2008) Sold, R.V., Rosas-Casals, M., Corominas-Murtre, B., Valverde, S.: Robustness of the European power grids under intentional attack. Phys. Rev. E 77(2), 026102 (2008)
19.
go back to reference Barabási, A.L., Albert, R., Jeong, H.: Mean-field theory for scale-free random networks. Phys. A: Stat. Mech. Appl. 272(1), 173–187 (1999)CrossRef Barabási, A.L., Albert, R., Jeong, H.: Mean-field theory for scale-free random networks. Phys. A: Stat. Mech. Appl. 272(1), 173–187 (1999)CrossRef
20.
21.
go back to reference Erdős, P., Rényi, A.: On the evolution of random graphs. Publ. Math. Inst. Hung. Acad. Sci. 5, 17–61 (1960)MathSciNetMATH Erdős, P., Rényi, A.: On the evolution of random graphs. Publ. Math. Inst. Hung. Acad. Sci. 5, 17–61 (1960)MathSciNetMATH
23.
go back to reference Goh, K.I., Kahng, B., Kim, D.: Universal behavior of load distribution in scale-free networks. Phys. Rev. Lett. 87, 287701 (2001)CrossRef Goh, K.I., Kahng, B., Kim, D.: Universal behavior of load distribution in scale-free networks. Phys. Rev. Lett. 87, 287701 (2001)CrossRef
24.
go back to reference Kalman, R.E.: Mathematical description of linear dynamical systems, J. Soc. Ind. Appl. Math. Series A: Control 1(2), 152–192 (1963)MathSciNetCrossRef Kalman, R.E.: Mathematical description of linear dynamical systems, J. Soc. Ind. Appl. Math. Series A: Control 1(2), 152–192 (1963)MathSciNetCrossRef
26.
go back to reference Hopcroft, J.E., Karp, R.M.: An n^5/2 algorithm for maximum matchings in bipartite graphs. SIAM J. Comput. 2(4), 225–231 (1973)MathSciNetCrossRef Hopcroft, J.E., Karp, R.M.: An n^5/2 algorithm for maximum matchings in bipartite graphs. SIAM J. Comput. 2(4), 225–231 (1973)MathSciNetCrossRef
27.
go back to reference Motter, A.E., Lai, Y.-C.: Cascade-based attacks on complex networks. Phys. Rev. E 66(6), 065102 (2002)CrossRef Motter, A.E., Lai, Y.-C.: Cascade-based attacks on complex networks. Phys. Rev. E 66(6), 065102 (2002)CrossRef
28.
go back to reference Motter, A.E.: Cascade control and defense in complex networks. Phys. Rev. E 93(9), 098701 (2004) Motter, A.E.: Cascade control and defense in complex networks. Phys. Rev. E 93(9), 098701 (2004)
29.
go back to reference Dou, B.-L., Wang, X.-G., Zhang, S.-Y.: Robustness of networks against cascading failures. Phys. A: Stat. Mech. Appl. 389(11), 2310–2317 (2010)CrossRef Dou, B.-L., Wang, X.-G., Zhang, S.-Y.: Robustness of networks against cascading failures. Phys. A: Stat. Mech. Appl. 389(11), 2310–2317 (2010)CrossRef
30.
go back to reference Wang, J.-W., Rong, L.-L.: A model for cascading failures in scale-free networks with a breakdown probability. Phys. A 388, 1289–1298 (2009)CrossRef Wang, J.-W., Rong, L.-L.: A model for cascading failures in scale-free networks with a breakdown probability. Phys. A 388, 1289–1298 (2009)CrossRef
31.
go back to reference Liu, J., Xiong, Q.Y., Shi, X., Wang, K., Shi, W.R.: Robustness of complex networks with an improved breakdown probability against cascading failures. Phys. A 456, 302–309 (2016)CrossRef Liu, J., Xiong, Q.Y., Shi, X., Wang, K., Shi, W.R.: Robustness of complex networks with an improved breakdown probability against cascading failures. Phys. A 456, 302–309 (2016)CrossRef
Metadata
Title
Robustness of Network Controllability Against Cascading Failure
Authors
Lv-lin Hou
Yan-dong Xiao
Liang Lu
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-030-36204-1_29

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