TY - JOUR
T1 - Robustness of synchronization to additive noise
T2 - How vulnerability depends on dynamics
AU - Porfiri, Maurizio
AU - Frasca, Mattia
N1 - Funding Information:
Manuscript received December 28, 2017; revised December 30, 2017 and March 17, 2018; accepted March 31, 2018. Date of publication April 9, 2018; date of current version March 14, 2019. This work was supported in part by the National Science Foundation under Grant CMMI 1561134 and in part by the U.S. Army Research Office under Grant W911NF-15-1-0267 with Dr. S. C. Stanton and Dr. A. Garcia as the Program Managers. Recommended by Associate Editor G. Russo. (Corresponding author: Maurizio Porfiri.) M. Porfiri is with the Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, Brooklyn NY 11201 USA (e-mail: [email protected]).
Publisher Copyright:
© 2014 IEEE.
PY - 2019/3
Y1 - 2019/3
N2 - From biological to technological networks, scientists and engineers must face the question of vulnerability to understand evolutionary processes or design-resilient systems. Here, we examine the vulnerability of a network of coupled dynamical units to failure or malfunction of one of its nodes. More specifically, we study the effect of additive noise that is injected at one of the network sites on the overall synchronization of the coupled dynamical systems. In the context of mean square stochastic stability, we present a mathematically principled approach to illuminate the interplay between dynamics and topology on network robustness. Through the new theoretical construct of robust metric, we uncover a complex and often counterintuitive effect of dynamics. While networks are more robust to noise injected at their hubs for a classical consensus problem, these hubs could become the most vulnerable nodes for higher order dynamics, such as second-order consensus and Rössler chaos. From the exact treatment of star networks and the systematic application of perturbation techniques, we offer a mechanistic explanation of these surprising results and lay the foundation for a theory of dynamic robustness of networks.
AB - From biological to technological networks, scientists and engineers must face the question of vulnerability to understand evolutionary processes or design-resilient systems. Here, we examine the vulnerability of a network of coupled dynamical units to failure or malfunction of one of its nodes. More specifically, we study the effect of additive noise that is injected at one of the network sites on the overall synchronization of the coupled dynamical systems. In the context of mean square stochastic stability, we present a mathematically principled approach to illuminate the interplay between dynamics and topology on network robustness. Through the new theoretical construct of robust metric, we uncover a complex and often counterintuitive effect of dynamics. While networks are more robust to noise injected at their hubs for a classical consensus problem, these hubs could become the most vulnerable nodes for higher order dynamics, such as second-order consensus and Rössler chaos. From the exact treatment of star networks and the systematic application of perturbation techniques, we offer a mechanistic explanation of these surprising results and lay the foundation for a theory of dynamic robustness of networks.
KW - Consensus
KW - information centrality
KW - mean square
KW - nonlinear
KW - perturbation
KW - stochastic stability
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U2 - 10.1109/TCNS.2018.2825024
DO - 10.1109/TCNS.2018.2825024
M3 - Article
AN - SCOPUS:85045204460
SN - 2325-5870
VL - 6
SP - 375
EP - 387
JO - IEEE Transactions on Control of Network Systems
JF - IEEE Transactions on Control of Network Systems
IS - 1
M1 - 8334260
ER -