arXiv subjects

Yamir Moreno

Publications and source records attributed to Yamir Moreno.

At least 181 records · Page 10Linked to original sources

arXiv2006

Immunization of Real Complex Communication Networks

Most communication networks are complex. In this paper, we address one of the fundamental problems we are facing nowadays, namely, how we can efficiently protect these networks. To this end, we study an immunization strategy and found that it works as good as targeted immunization, but using only local information about the network topology. Our findings are supported with numerical simulations of the Susceptible-Infected-Removed (SIR) model on top of real communication networks, where immune nodes are previously identified by a covering algorithm. The results provide useful hints in the way to design and deploying a digital immune system.

physics.soc-ph↗

arXiv2005

Critical threshold and dynamics of a general rumor model on complex networks

We derive mean-field equations that describe the dynamics of a general model of rumor spreading on complex networks, and use analytical and numerical solutions of these equations to examine the threshold behavior and dynamics of the model on random graphs, uncorrelated scale-free networks and scale-free networks with assortative degree correlations. We show that in both homogeneous networks and random graphs the model exhibits a critical threshold in the rumor spreading rate below which a rumor cannot propagate in the system. In the case of scale-free networks, on the other hand, this threshold becomes vanishingly small in the limit of infinite system size. We find that the initial rate at which a rumor spreads is much higher in scale-free networks than in random graphs, and that the rate at which the spreading proceeds on scale-free networks is further increased when assortative degree correlations are introduced. The impact of degree correlations on the final fraction of nodes that ever hears a rumor, however, depends on the interplay between network topology and the rumor spreading rate. Our results show that scale-free networks are prone to the spreading of rumors, just as they are to the spreading of infections. They are relevant to the spreading dynamics of chain emails, viral advertising and large-scale data dissemination algorithms on the Internet, the so-called gossip protocols.

physics.soc-ph↗

arXiv2005

Michaelis-Menten Dynamics in Complex Heterogeneous Networks

Biological networks have been recently found to exhibit many topological properties of the so-called complex networks. It has been reported that they are, in general, both highly skewed and directed. In this paper, we report on the dynamics of a Michaelis-Menten like model when the topological features of the underlying network resemble those of real biological networks. Specifically, instead of using a random graph topology, we deal with a complex heterogeneous network characterized by a power-law degree distribution coupled to a continuous dynamics for each network's component. The dynamics of the model is very rich and stationary, periodic and chaotic states are observed upon variation of the model's parameters. We characterize these states numerically and report on several quantities such as the system's phase diagram and size distributions of clusters of stationary, periodic and chaotic nodes. The results are discussed in view of recent debate about the ubiquity of complex networks in nature and on the basis of several biological processes that can be well described by the dynamics studied.

q-bio.MN↗

arXiv2005

Distance-d covering problems in scale-free networks with degree correlations

A number of problems in communication systems demand the distributed allocation of network resources in order to provide better services, sampling and distribution methods. The solution to these issues is becoming more challenging due to the increasing size and complexity of communication networks. We report here on an heuristic method that allows to find near-optimal solutions to the covering problem in real communication networks. The results show that the optimal allocation of resources strongly depends on the topology of the underlying networks. Whether a centralized or distributed design is to be used relies upon the degree correlations between connected vertices.

cond-mat.stat-mech↗

arXiv2004

Dynamics of jamming transitions in complex networks

We numerically investigate jamming transitions in complex heterogeneous networks. Inspired by Internet routing protocols, we study a general model that incorporates local traffic information through a tunable parameter. The results show that whether the transition from a low-traffic regime to a congested phase is of first or second order type is determined by the protocol at work. The microscopic dynamics reveals that these two radically different behaviors are due to the way in which traffic jams propagate through the network. Our results are discussed in the context of Internet dynamics and other transport processes that take place on complex networks and provide insights for the design of routing policies based on traffic awareness in communication systems.

cond-mat.stat-mech↗

arXiv2004

Improved routing strategies for Internet traffic delivery

We analyze different strategies aimed at optimizing routing policies in the Internet. We first show that for a simple deterministic algorithm the local properties of the network deeply influence the time needed for packet delivery between two arbitrarily chosen nodes. We next rely on a real Internet map at the autonomous system level and introduce a score function that allows us to examine different routing protocols and their efficiency in traffic handling and packet delivery. Our results suggest that actual mechanisms are not the most efficient and that they can be integrated in a more general, though not too complex, scheme.

cond-mat.other↗

arXiv2004

Synchronization of Kuramoto Oscillators in Scale-Free Networks

In this work, we study the synchronization of coupled phase oscillators on the underlying topology of scale-free networks. In particular, we assume that each network's component is an oscillator and that each interacts with the others following the Kuramoto model. We then study the onset of global phase synchronization and fully characterize the system's dynamics. We also found that the resynchronization time of a perturbed node decays as a power law of its connectivity, providing a simple analytical explanation to this interesting behavior.

cond-mat.stat-mech↗

arXiv2004

Dynamics of Rumor Spreading in Complex Networks

We derive the mean-field equations characterizing the dynamics of a rumor process that takes place on top of complex heterogeneous networks. These equations are solved numerically by means of a stochastic approach. First, we present analytical and Monte Carlo calculations for homogeneous networks and compare the results with those obtained by the numerical method. Then, we study the spreading process in detail for random scale-free networks. The time profiles for several quantities are numerically computed, which allow us to distinguish among different variants of rumor spreading algorithms. Our conclusions are directed to possible applications in replicated database maintenance, peer to peer communication networks and social spreading phenomena.

cond-mat.stat-mech↗

arXiv2004

Fitness for Synchronization of Network Motifs

We study the phase synchronization of Kuramoto's oscillators in small parts of networks known as motifs. We first report on the system dynamics for the case of a scale-free network and show the existence of a non-trivial critical point. We compute the probability that network motifs synchronize, and find that the fitness for synchronization correlates well with motif's interconnectedness and structural complexity. Possible implications for present debates about network evolution in biological and other systems are discussed.

cond-mat.stat-mech↗

arXiv2004

Local versus Global Knowledge in the Barabasi-Albert scale-free network model

The scale-free model of Barabasi and Albert gave rise to a burst of activity in the field of complex networks. In this paper, we revisit one of the main assumptions of the model, the preferential attachment rule. We study a model in which the PA rule is applied to a neighborhood of newly created nodes and thus no global knowledge of the network is assumed. We numerically show that global properties of the BA model such as the connectivity distribution and the average shortest path length are quite robust when there is some degree of local knowledge. In contrast, other properties such as the clustering coefficient and degree-degree correlations differ and approach the values measured for real-world networks.

cond-mat.stat-mech↗

arXiv2003

Efficiency and reliability of epidemic data dissemination in complex networks

We study the dynamics of epidemic spreading processes aimed at spontaneous dissemination of information updates in populations with complex connectivity patterns. The influence of the topological structure of the network in these processes is studied by analyzing the behavior of several global parameters such as reliability, efficiency and load. Large scale numerical simulations of update spreading processes show that while networks with homogeneous connectivity patterns permit a higher reliability, scale-free topologies allow for a better efficiency.

cond-mat.stat-mech↗

arXiv2003

Epidemic Incidence in Correlated Complex Networks

We introduce a numerical method to solve epidemic models on the underlying topology of complex networks. The approach exploits the mean-field like rate equations describing the system and allows to work with very large system sizes, where Monte Carlo simulations are useless due to memory needs. We then study the SIR epidemiological model on assortative networks, providing numerical evidence of the absence of epidemic thresholds. Besides, the time profiles of the populations are analyzed. Finally, we stress that the present method would allow to solve arbitrary epidemic-like models provided that they can be described by mean-field rate equations.

cond-mat.stat-mech↗

arXiv2003

Error Diagrams and Temporal Correlations in a Fracture Model with Characteristic and Power-Law Distributed Avalanches

Forecasting failure events is one of the most important problems in fracture mechanics and related sciences. In this paper, we use the Molchan scheme to investigate the error diagrams in a fracture model which has the notable advantage of displaying two completely different regimes according to the heterogeneity of the system. In one regime, a characteristic event is observed while for the second regime a power-law spectrum of avalanches is obtained reminiscent of self-organized criticality. We find that both regimes are different when predicting large avalanches and that, in the second regime, there are non-trivial temporal correlations associated to clustering of large events. Finally, we extend the discussion to seismology, where both kinds of avalanche size distributions can be seen.

cond-mat.stat-mech↗

arXiv2003

Resilience to damage of graphs with degree correlations

The existence or not of a percolation threshold on power law correlated graphs is a fundamental question for which a general criterion is lacking. In this work we investigate the problems of site and bond percolation on graphs with degree correlations and their connection with spreading phenomena. We obtain some general expressions that allow the computation of the transition thresholds or their bounds. Using these results we study the effects of assortative and disassortative correlations on the resilience to damage of networks.

cond-mat.dis-nn↗

arXiv2002

Universality classes in creep rupture

We study the creep response of solids to a constant external load in the framework of a novel fiber bundle model introduced. Analytical and numerical calculations showed that increasing the external load on a specimen a transition takes place from a partially failed state of infinite lifetime to a state where global failure occurs at a finite time. Two universality classes of creep rupture were identified depending on the range of interaction of fibers: in the mean field limit the transition between the two states is continuous characterized by power law divergences, while for local interactions it becomes abrupt with no scaling. Varying the range of interaction a sharp transition is revealed between the mean field and short range regimes. The creeping system evolves into a macroscopic stationary state accompanied by the emergence of a power law distribution of inter-event times of the microscopic relaxation process, which indicates self organized criticality in creep.

cond-mat.stat-mech↗

arXiv2002

Disease Spreading in Structured Scale-Free Networks

We study the spreading of a disease on top of structured scale-free networks recently introduced. By means of numerical simulations we analyze the SIS and the SIR models. Our results show that when the connectivity fluctuations of the network are unbounded whether the epidemic threshold exists strongly depends on the initial density of infected individuals and the type of epidemiological model considered. Analytical arguments are provided in order to account for the observed behavior. We conclude that the peculiar topological features of this network and the absence of small-world properties determine the dynamics of epidemic spreading.

cond-mat.stat-mech↗

arXiv2002

Time evolution of damage under variable ranges of load transfer

We study the time evolution of damage in a fiber bundle model in which the range of interaction of fibers varies through an adjustable stress transfer function recently introduced. We find that the lifetime of the material exhibits a crossover from mean field to short range behavior as in the static case. Numerical calculations showed that the value at which the transition takes place depends on the system's disorder. Finally, we have performed a microscopic analysis of the failure process. Our results confirm that the growth dynamics of the largest crack is radically different in the two limiting regimes of load transfer during the first stages of breaking.

cond-mat.stat-mech↗

arXiv2002

Topology and correlations in structured scale-free networks

We study a recently introduced class of scale-free networks showing a high clustering coefficient and non-trivial connectivity correlations. We find that the connectivity probability distribution strongly depends on the fine details of the model. We solve exactly the case of low average connectivity, providing also exact expressions for the clustering and degree correlation functions. The model also exhibits a lack of small world properties in the whole parameters range. We discuss the physical properties of these networks in the light of the present detailed analysis.

cond-mat.stat-mech↗