Download PDF by Dror Y. Kenett, Jianxi Gao, Xuqing Huang, Shuai Shao, Irena: Networks of Networks: The Last Frontier of Complexity

By Dror Y. Kenett, Jianxi Gao, Xuqing Huang, Shuai Shao, Irena Vodenska (auth.), Gregorio D'Agostino, Antonio Scala (eds.)

ISBN-10: 3319035177

ISBN-13: 9783319035178

ISBN-10: 3319035185

ISBN-13: 9783319035185

The current paintings is intended as a connection with offer an natural and entire view of the main correct ends up in the fascinating new box of Networks of Networks (NetoNets). Seminal papers have lately been released posing the root to check what occurs while various networks engage, therefore offering facts for the emergence of recent, unforeseen behaviors and vulnerabilities. From these seminal works, the attention at the value figuring out Networks of Networks (NetoNets) has unfold to the full group of Complexity technological know-how. The reader will enjoy the event of a few of the main well-recognized leaders during this box. The contents were aggregated less than 4 headings; normal thought, Phenomenology, functions and threat evaluation. The reader can be inspired by way of the various functions of the final paradigm that span from body structure, to monetary probability, to transports. we're at present making the 1st steps to minimize the gap among the language and how of deliberating the 2 groups of specialists in actual infrastructures and the complexity scientists. even supposing this direction could turn out to be lengthy, this can be very promising, either in extending our realizing of complicated structures and to find concrete purposes that may improve the existence caliber of thousands of people.

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Additional info for Networks of Networks: The Last Frontier of Complexity

Sample text

Recent studies have shown that, for single isolated networks, both bond percolation and site percolation have percolation and epidemic thresholds that are higher than those in unclustered networks [68–73]. Here we review a mathematical framework for understanding how the robustness of interdependent networks is affected by clustering within the network components. We extend the percolation method developed by Newman [68] for single clustered networks to coupled clustered networks. Huang et al. [65] found that interdependent networks that exhibit significant clustering are more vulnerable to random node failure than networks with low significant clustering.

Upper panel: illustration of bank-node and asset-node. Bi,m is the amount of asset m that bank i owns. Thus, a bank i with total asset value Bi has wi,m fraction of its total asset value in asset m. si,m is the fraction of asset m that the bank holds out. Lower panel: illustration of the cascading failure process. The rectangles represent the assets and the circles represent the banks. From left to right, initially, an asset suffers loss in value which causes all the related banks’ total assets to shrink.

Balcan, V. Colizza, B. Gonçalves, H. J. Ramasco, A. Vespignani, Proceedings of the National Academy of Sciences 106(51), 21484 (2009) 39. G. Palla, I. Derényi, I. Farkas, T. Vicsek, Nature 435(7043), 814 (2005) 40. G. J. Watts, Science 311(5757), 88 (2006) 41. J. Newman, Proceedings of the National Academy of Sciences 98(2), 404 (2001) 42. A. S. J. O. Indekeu, Physical Review Letters 102(1), 018701 (2009) 43. S. Y. Kenett, E. Ben-Jacob, A. Bunde, R. Cohen, H. Hermann, J. Kantelhardt, J. Kertész, S.

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Networks of Networks: The Last Frontier of Complexity by Dror Y. Kenett, Jianxi Gao, Xuqing Huang, Shuai Shao, Irena Vodenska (auth.), Gregorio D'Agostino, Antonio Scala (eds.)


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