[en] Motivated by applications in biology and economics, we propose new volatility measures based on the H2 system norm for linear networks stimulated by independent or correlated noise. We identify critical links in a network, where relatively small improvements can lead to large reductions in network volatility measures. We also examine volatility measures of individual nodes and their dependence on the topological position in the network. Finally, we investigate the dependence of the volatility on different network interconnections, weights of the edges and other network properties. Hence in an intuitive and efficient way, we can identify critical links,
nodes and interconnections in network which can shed light in the network design to make it more robust.
Centre de recherche :
- Luxembourg Centre for Systems Biomedicine (LCSB): Systems Control (Goncalves Group)
Disciplines :
Ingénierie, informatique & technologie: Multidisciplinaire, généralités & autres
Auteur, co-auteur :
Huang, Qingqing
Yuan, Ye
GONCALVES, Jorge ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Dahleh, Munther
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
H2 Norm Based Network Volatility Measures
Date de publication/diffusion :
2014
Nom de la manifestation :
American Control Conference
Lieu de la manifestation :
Portland, Oregon, Etats-Unis
Date de la manifestation :
June 4-6, 2014
Titre de l'ouvrage principal :
The proceedings of the American Control Conference
J. C. Doyle and M. Csete, "Architecture, constraints, and behavior", Proceedings of the National Academy of Sciences, vol. 108, no. Supplement 3, pp. 15 624-15 630, 2011.
H. Kitano, "Biological robustness", Nature Reviews Genetics, vol. 5, no. 11, pp. 826-837, 2004.
D. Acemoglu, V. M. Carvalho, A. Ozdaglar, and A. Tahbaz-Salehi, "The network origins of aggregate fluctuations", Econometrica, vol. 80, no. 5, pp. 1977-2016, 2012.
G. F. Young, L. Scardovi, and N. E. Leonard, "Robustness of noisy consensus dynamics with directed communication", in American Control Conference (ACC), 2010. IEEE, 2010, pp. 6312-6317.
D. Zelazo and M. Mesbahi, "Graph-theoretic methods for networked dynamic systems: Heterogeneity and h 2 performance", in Efficient Modeling and Control of Large-Scale Systems. Springer, 2010.
M. Siami and N. Motee, "Fundamental limits on robustness measures in networks of interconnected systems", in Conference on Decision and Control (CDC), 2013. IEEE, 2013.
E. Estrada and N. Hatano, "A vibrational approach to node centrality and vulnerability in complex networks", Physica A: Statistical Mechanics and its Applications, vol. 389, no. 17, pp. 3648-3660, 2010.
Y.-Y. Liu, J.-J. Slotine, and A.-L. Barabási, " Controllability of complex networks", Nature, vol. 473, no. 7346, pp. 167-173, 2011.
G. E. Dullerud and F. Paganini, A course in robust control theory. Springer New York, 2000, vol. 6.
N. Rosenfeld, J. W. Young, U. Alon, P. S. Swain, and M. B. Elowitz, "Gene regulation at the single-cell level", Science, vol. 307, no. 5717, pp. 1962-1965, 2005.
M. J. Dunlop, R. S. Cox, J. H. Levine, R. M. Murray, and M. B. Elowitz, "Regulatory activity revealed by dynamic correlations in gene expression noise", Nature genetics, vol. 40, no. 12, 2008.
A. Pothen, H. D. Simon, and K.-P. Liou, "Partitioning sparse matrices with eigenvectors of graphs", SIAM Journal on Matrix Analysis and Applications, vol. 11, no. 3, pp. 430-452, 1990.
J. P. Gleeson, "Cascades on correlated and modular random networks", Phys. Rev. E, 2008.
M. Catanzaro and R. Pastor-Satorras, "Analytic solution of a static scale-free network model", The European Physical Journal B-Condensed Matter and Complex Systems, vol. 44, no. 2, 2005.
W. Ellens, F. Spieksma, P. Van Mieghem, A. Jamakovic, and R. Kooij, "Effective graph resistance", Linear algebra and its applications, vol. 435, no. 10, pp. 2491-2506, 2011.
