Coherence Scaling of Noisy Second-Order Scale-Free Consensus Networks

A striking discovery in the field of network science is that the majority of real networked systems have some universal structural properties. In generally, they are simultaneously sparse, scale-free, small-world, and loopy. In this paper, we investigate the second-order consensus of dynamic networks with such universal structures subject to white noise at vertices. We focus on the network coherence HSO characterized in terms of the H2-norm of the vertex systems, which measures the mean deviation of vertex states from their average value. We first study numerically the coherence of some representative real-world networks. We find that their coherence HSO scales sublinearly with the vertex number N . We then study analytically HSO for a class of iteratively growing networks—pseudofractal scalefree webs (PSFWs), and obtain an exact solution to HSO, which also increases sublinearly in N , with an exponent much smaller than 1. To explain the reasons for this sublinear behavior, we finally study HSO for Sierpinśki gaskets, for which HSO grows superlinearly in N , with a power exponent much larger than 1. Sierpinśki gaskets have the same number of vertices and edges as the PSFWs, but do not display the scale-free and small-world properties. We thus conclude that the scale-free and small-world, and loopy topologies are jointly responsible for the observed sublinear scaling of HSO.

[1]  A. Vespignani,et al.  The architecture of complex weighted networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[2]  Xiaofeng Liao,et al.  A Nesterov-Like Gradient Tracking Algorithm for Distributed Optimization Over Directed Networks , 2021, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[3]  R. Olfati-Saber Ultrafast consensus in small-world networks , 2005, Proceedings of the 2005, American Control Conference, 2005..

[4]  Tingwen Huang,et al.  Convergence Analysis of a Distributed Optimization Algorithm with a General Unbalanced Directed Communication Network , 2019, IEEE Transactions on Network Science and Engineering.

[5]  Bassam Bamieh,et al.  Network coherence in fractal graphs , 2011, IEEE Conference on Decision and Control and European Control Conference.

[6]  Ralf Diekmann,et al.  Efficient schemes for nearest neighbor load balancing , 1999, Parallel Comput..

[7]  Zhongzhi Zhang,et al.  Domination number and minimum dominating sets in pseudofractal scale-free web and Sierpiński graph , 2017, Theor. Comput. Sci..

[8]  Reza Olfati-Saber,et al.  Flocking for multi-agent dynamic systems: algorithms and theory , 2006, IEEE Transactions on Automatic Control.

[9]  Dimos V. Dimarogonas,et al.  On the Rendezvous Problem for Multiple Nonholonomic Agents , 2007, IEEE Transactions on Automatic Control.

[10]  R. Merris Laplacian graph eigenvectors , 1998 .

[11]  Tao Xiang,et al.  Privacy Masking Stochastic Subgradient-Push Algorithm for Distributed Online Optimization , 2020, IEEE Transactions on Cybernetics.

[12]  Stephen P. Boyd,et al.  Distributed average consensus with least-mean-square deviation , 2007, J. Parallel Distributed Comput..

[13]  Stephen P. Boyd,et al.  Minimizing Effective Resistance of a Graph , 2008, SIAM Rev..

[14]  Mark Newman,et al.  Networks: An Introduction , 2010 .

[15]  Bassam Bamieh,et al.  Leader selection for optimal network coherence , 2010, 49th IEEE Conference on Decision and Control (CDC).

[16]  Qun Li,et al.  Global clock synchronization in sensor networks , 2006, IEEE Transactions on Computers.

[17]  Jérôme Kunegis,et al.  KONECT: the Koblenz network collection , 2013, WWW.

[18]  Thomas A. Funkhouser,et al.  Biharmonic distance , 2010, TOGS.

[19]  Zhongzhi Zhang,et al.  Independence number and the number of maximum independent sets in pseudofractal scale-free web and Sierpiński gasket , 2018, Theor. Comput. Sci..

[20]  Yuming Jiang,et al.  Approximate Consensus in Stochastic Networks With Application to Load Balancing , 2015, IEEE Transactions on Information Theory.

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

[22]  Yi Qi,et al.  Extended corona product as an exactly tractable model for weighted heterogeneous networks , 2017, Comput. J..

[23]  M. Randic,et al.  Resistance distance , 1993 .

[24]  Bassam Bamieh,et al.  Coherence in Large-Scale Networks: Dimension-Dependent Limitations of Local Feedback , 2011, IEEE Transactions on Automatic Control.

[25]  T. Coletta,et al.  Robustness of Synchrony in Complex Networks and Generalized Kirchhoff Indices. , 2017, Physical review letters.

[26]  Jinde Cao,et al.  Distributed Consensus of Stochastic Delayed Multi-agent Systems Under Asynchronous Switching , 2016, IEEE Transactions on Cybernetics.

[27]  Ella M. Atkins,et al.  Second-order Consensus Protocols in Multiple Vehicle Systems with Local Interactions , 2005 .

[28]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[29]  Sébastien Motsch,et al.  Heterophilious Dynamics Enhances Consensus , 2013, SIAM Rev..

[30]  Guanrong Chen,et al.  Robustness of First- and Second-Order Consensus Algorithms for a Noisy Scale-Free Small-World Koch Network , 2017, IEEE Transactions on Control Systems Technology.

[31]  Mihailo R. Jovanovic,et al.  Effect of topological dimension on rigidity of vehicle formations: Fundamental limitations of local feedback , 2008, 2008 47th IEEE Conference on Decision and Control.

[32]  Nader Motee,et al.  Time-Delay Origins of Fundamental Tradeoffs Between Risk of Large Fluctuations and Network Connectivity , 2018, IEEE Transactions on Automatic Control.

[33]  Frank Allgöwer,et al.  Delay robustness in consensus problems , 2010, Autom..

[34]  Zhongzhi Zhang,et al.  Farey graphs as models for complex networks , 2011, Theor. Comput. Sci..

[35]  Bin Wu,et al.  Counting spanning trees in a small-world Farey graph , 2012, 1201.4228.

[36]  Jinde Cao,et al.  Distributed Parametric Consensus Optimization With an Application to Model Predictive Consensus Problem , 2018, IEEE Transactions on Cybernetics.

[37]  Peter F Stadler,et al.  Statistics of cycles in large networks. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[38]  Bassam Bamieh,et al.  Consensus and Coherence in Fractal Networks , 2013, IEEE Transactions on Control of Network Systems.

[39]  Xin-Ping Guan,et al.  Distributed optimal consensus filter for target tracking in heterogeneous sensor networks , 2011, 2011 8th Asian Control Conference (ASCC).

[40]  Zhongzhi Zhang,et al.  On the spectrum of the normalized Laplacian of iterated triangulations of graphs , 2015, Appl. Math. Comput..

[41]  Stacy Patterson,et al.  Scale-Free Loopy Structure is Resistant to Noise in Consensus Dynamics in Complex Networks , 2018, IEEE Transactions on Cybernetics.

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

[43]  Kenneth E. Barner,et al.  Convergence of Consensus Models With Stochastic Disturbances , 2010, IEEE Transactions on Information Theory.

[44]  Wenwu Yu,et al.  Distributed Consensus Filtering in Sensor Networks , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[45]  Yi Qi,et al.  Consensus in Self-Similar Hierarchical Graphs and Sierpiński Graphs: Convergence Speed, Delay Robustness, and Coherence , 2017, IEEE Transactions on Cybernetics.

[46]  Stacy Patterson,et al.  Biharmonic Distance and Performance of Second-Order Consensus Networks with Stochastic Disturbances , 2017, 2018 Annual American Control Conference (ACC).

[47]  Miroslaw Malek,et al.  The consensus problem in fault-tolerant computing , 1993, CSUR.

[48]  Guanrong Chen,et al.  Small-World Topology Can Significantly Improve the Performance of Noisy Consensus in a Complex Network , 2015, Comput. J..

[49]  John N. Tsitsiklis,et al.  Convergence Speed in Distributed Consensus and Averaging , 2009, SIAM J. Control. Optim..

[50]  Ruggero Carli,et al.  Network Clock Synchronization Based on the Second-Order Linear Consensus Algorithm , 2014, IEEE Transactions on Automatic Control.

[51]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.

[52]  Choujun Zhan,et al.  On the distributions of Laplacian eigenvalues versus node degrees in complex networks , 2010 .

[53]  Naomi Ehrich Leonard,et al.  Robustness of noisy consensus dynamics with directed communication , 2010, Proceedings of the 2010 American Control Conference.

[54]  Wenwu Yu,et al.  An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination , 2012, IEEE Transactions on Industrial Informatics.

[55]  S. N. Dorogovtsev,et al.  Pseudofractal scale-free web. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[56]  Hernán D. Rozenfeld,et al.  Statistics of cycles: how loopy is your network? , 2004, cond-mat/0403536.