Since its first use by Euler on the problem of the seven bridges of Königsberg, graph theory
has shown excellent abilities in solving and unveiling the properties of multiple discrete …

Graph-based models form a fundamental aspect of data representation in Data Sciences
and play a key role in modeling complex networked systems. In particular, recently there is …

We propose a method for the Distributed Assessment of the Closeness CEntrality Ranking
(DACCER) in complex networks. DACCER computes centrality based only on localized …

Information diffusion has been widely discussed in various disciplines including sociology,
economics, physics or computer science. In this paper, we generalize the linear threshold …

Graph-based models form a fundamental aspect of data representation in Data Sciences
and play a key role in modeling complex networked systems. In particular, recently there is …

A crucial feature in implementing the next generation of smart grids is how to introduce self-
healing capabilities allowing to ensure a high quality of service to the users. We show how …

Diffusion processes in complex dynamic networks can arise, for instance, on data search,
data routing, and information spreading. Therefore, understanding how to speed up the …

We present some possible Complex Networks approaches to study and understand Power
Grids and to improve them into Smart Grids. We first sketch the general properties of the …

Large software may be modeled as graphs in several ways. For instance, nodes may
represent modules, objects or functions, and links may encode dependencies between …

Nós propomos um novo modelo para grafos variantes no tempo (GVTs), adequados para a
representação de redes dinâmicas, por exemplo. Mostramos que o modelo proposto é …