Exact controllability of multiplex networks

We develop a general framework to analyze the controllability of multiplex networks using multiple-relation networks and multiple-layer networks with interlayer couplings as two classes of prototypical systems. In the former, networks associated with different physical variables share the same set of nodes and in the latter, diffusion processes take place. We find that, for a multiple-relation network, a layer exists that dominantly determines the controllability of the whole network and, for a multiple-layer network, a small fraction of the interconnections can enhance the controllability remarkably. Our theory is generally applicable to other types of multiplex networks as well, leading to significant insights into the control of complex network systems with diverse structures and interacting patterns.

[1]  H. Stanley,et al.  Networks formed from interdependent networks , 2011, Nature Physics.

[2]  Y. Lai,et al.  Optimizing controllability of complex networks by minimum structural perturbations. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[3]  E. Ott,et al.  Synchronization in networks of networks: the onset of coherent collective behavior in systems of interacting populations of heterogeneous oscillators. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  Wen-Xu Wang,et al.  Exact controllability of complex networks , 2013, Nature Communications.

[5]  Conrado J. Pérez Vicente,et al.  Diffusion dynamics on multiplex networks , 2012, Physical review letters.

[6]  M. Mézard,et al.  The Bethe lattice spin glass revisited , 2000, cond-mat/0009418.

[7]  Lenka Zdeborová,et al.  The number of matchings in random graphs , 2006, ArXiv.

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

[9]  Zhi-Xi Wu,et al.  Cooperation enhanced by the difference between interaction and learning neighborhoods for evolutionary spatial prisoner's dilemma games. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[10]  H. Ohtsuki,et al.  Breaking the symmetry between interaction and replacement in evolutionary dynamics on graphs. , 2007, Physical review letters.

[11]  Alan M. Frieze,et al.  Random graphs , 2006, SODA '06.

[12]  Albert-László Barabási,et al.  Control Centrality and Hierarchical Structure in Complex Networks , 2012, PloS one.

[13]  Harry Eugene Stanley,et al.  Catastrophic cascade of failures in interdependent networks , 2009, Nature.

[14]  Jukka-Pekka Onnela,et al.  Community Structure in Time-Dependent, Multiscale, and Multiplex Networks , 2009, Science.

[15]  R. Kálmán Mathematical description of linear dynamical systems , 1963 .

[16]  Jung Yeol Kim,et al.  Correlated multiplexity and connectivity of multiplex random networks , 2011, 1111.0107.

[17]  Harry Eugene Stanley,et al.  Robustness of a Network of Networks , 2010, Physical review letters.

[18]  Ching-tai Lin Structural controllability , 1974 .

[19]  Wenwu Yu,et al.  Distributed Higher Order Consensus Protocols in Multiagent Dynamical Systems , 2011, IEEE Transactions on Circuits and Systems I: Regular Papers.

[20]  Tamás Vicsek,et al.  Controlling edge dynamics in complex networks , 2011, Nature Physics.

[21]  Albert-László Barabási,et al.  Controllability of complex networks , 2011, Nature.

[22]  Ljupco Kocarev,et al.  Discrete-time distributed consensus on multiplex networks , 2014 .

[23]  F. Garofalo,et al.  Controllability of complex networks via pinning. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[24]  Sergey V. Buldyrev,et al.  Critical effect of dependency groups on the function of networks , 2010, Proceedings of the National Academy of Sciences.

[25]  Jie Ren,et al.  Controlling complex networks: How much energy is needed? , 2012, Physical review letters.

[26]  Marc Barthelemy,et al.  Spatial Networks , 2010, Encyclopedia of Social Network Analysis and Mining.

[27]  M.L.J. Hautus,et al.  Controllability and observability conditions of linear autonomous systems , 1969 .

[28]  M. Newman,et al.  Renormalization Group Analysis of the Small-World Network Model , 1999, cond-mat/9903357.

[29]  R. Dobson Introduction To First Edition , 1983 .

[30]  A. Arenas,et al.  Stability of Boolean multilevel networks. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.