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A mathematical study of cascading failures in complex systems through graph invariants and centralities: Applications to real networks

Total activity: 3
Type of activity
Competitive project
Funding entity
Funding entity code
32.428,00 €
Start date
End date
algorithms, algoritmos, cascading failures, combinatoria, combinatorics, communication, comunicación, fallos en cascada, grafos, graph theory, networks, optimización, optimization, redes
Many real complex systems (e.g. communication, transportation, social and biological networks) are studied mathematically by using tools
from graph theory. These systems, modeled as networks with weighted nodes and links, share many properties like that they are smallworld
(short average distance), scale-free (adding now nodes does not change the main characteristics) and modular. These properties
make them quite sensitive to cascading failures, as the failure of one or several nodes propagates easily and leads to a total collapse of
the system. It is really important to prevent cascade failures like those which happened in recent years to the global router network, the
European electrical network, and Facebook. Even illnesses can be associated to cascading failures in the human interactome (network of
protein interactions). The approach to this problem in the current literature is essentially descriptive and based on simulations. With the aim
to understand the cascading failure process and also to find efficient methods of protection, we will apply our graph theory and algorithmic
knowledge to study it mathematically on model graphs and from real networks data the power grid and airport networks of EU and USA,
the human interactome, and other public available data-. We plan to determine which vertex sets, graph invariants and parameters are
relevant in the cascading failure process and we will propose methods and algorithms to control this catastrophic process. We are
particularly interested in the role that vertices from different centrality sets (including domination sets) play as triggers of the failures and
which changes would produce a resilient network. Our team has a relevant and complementary experience in different aspects of discrete
mathematics (graph theory and algorithmics), with experience in technical and biological applications which should contribute to the
success of this project.
Adm. Estat
Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020
Resoluton year
Funcding program
Programa Estatal de Generación de Conocimiento y Fortalecimiento Científico y Tecnológico del Sistema de I+D+i
Funding subprogram
Subprograma Estatal de Generación de Conocimiento
Funding call
Proyectos de I+D de generación de conocimiento (antigues EXC)
Grant institution
Agencia Estatal De Investigacion


Scientific and technological production

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