18,262 research outputs found
Diffusion geometry unravels the emergence of functional clusters in collective phenomena
Collective phenomena emerge from the interaction of natural or artificial
units with a complex organization. The interplay between structural patterns
and dynamics might induce functional clusters that, in general, are different
from topological ones. In biological systems, like the human brain, the overall
functionality is often favored by the interplay between connectivity and
synchronization dynamics, with functional clusters that do not coincide with
anatomical modules in most cases. In social, socio-technical and engineering
systems, the quest for consensus favors the emergence of clusters.
Despite the unquestionable evidence for mesoscale organization of many
complex systems and the heterogeneity of their inter-connectivity, a way to
predict and identify the emergence of functional modules in collective
phenomena continues to elude us. Here, we propose an approach based on random
walk dynamics to define the diffusion distance between any pair of units in a
networked system. Such a metric allows to exploit the underlying diffusion
geometry to provide a unifying framework for the intimate relationship between
metastable synchronization, consensus and random search dynamics in complex
networks, pinpointing the functional mesoscale organization of synthetic and
biological systems.Comment: 9 pages, 7 figure
Distance entropy cartography characterises centrality in complex networks
We introduce distance entropy as a measure of homogeneity in the distribution
of path lengths between a given node and its neighbours in a complex network.
Distance entropy defines a new centrality measure whose properties are
investigated for a variety of synthetic network models. By coupling distance
entropy information with closeness centrality, we introduce a network
cartography which allows one to reduce the degeneracy of ranking based on
closeness alone. We apply this methodology to the empirical multiplex lexical
network encoding the linguistic relationships known to English speaking
toddlers. We show that the distance entropy cartography better predicts how
children learn words compared to closeness centrality. Our results highlight
the importance of distance entropy for gaining insights from distance patterns
in complex networks.Comment: 11 page
The fragility of decentralised trustless socio-technical systems
The blockchain technology promises to transform finance, money and even governments. However, analyses of blockchain applicability and robustness typically focus on isolated systems whose actors contribute mainly by running the consensus algorithm. Here, we highlight the importance of considering trustless platforms within the broader ecosystem that includes social and communication networks. As an example, we analyse the flash-crash observed on 21st June 2017 in the Ethereum platform and show that a major phenomenon of social coordination led to a catastrophic cascade of events across several interconnected systems. We propose the concept of “emergent centralisation” to describe situations where a single system becomes critically important for the functioning of the whole ecosystem, and argue that such situations are likely to become more and more frequent in interconnected socio-technical systems. We anticipate that the systemic approach we propose will have implications for future assessments of trustless systems and call for the attention of policy-makers on the fragility of our interconnected and rapidly changing world
Fast detection of nonlinearity and nonstationarity in short and noisy time series
We introduce a statistical method to detect nonlinearity and nonstationarity
in time series, that works even for short sequences and in presence of noise.
The method has a discrimination power similar to that of the most advanced
estimators on the market, yet it depends only on one parameter, is easier to
implement and faster. Applications to real data sets reject the null hypothesis
of an underlying stationary linear stochastic process with a higher confidence
interval than the best known nonlinear discriminators up to date.Comment: 5 pages, 6 figure
Modeling Structure and Resilience of the Dark Network
While the statistical and resilience properties of the Internet are no more
changing significantly across time, the Darknet, a network devoted to keep
anonymous its traffic, still experiences rapid changes to improve the security
of its users. Here, we study the structure of the Darknet and we find that its
topology is rather peculiar, being characterized by non-homogenous distribution
of connections -- typical of scale-free networks --, very short path lengths
and high clustering -- typical of small-world networks -- and lack of a core of
highly connected nodes.
We propose a model to reproduce such features, demonstrating that the
mechanisms used to improve cyber-security are responsible for the observed
topology. Unexpectedly, we reveal that its peculiar structure makes the Darknet
much more resilient than the Internet -- used as a benchmark for comparison at
a descriptive level -- to random failures, targeted attacks and cascade
failures, as a result of adaptive changes in response to the attempts of
dismantling the network across time.Comment: 8 pages, 5 figure
Influence of augmented humans in online interactions during voting events
The advent of the digital era provided a fertile ground for the development
of virtual societies, complex systems influencing real-world dynamics.
Understanding online human behavior and its relevance beyond the digital
boundaries is still an open challenge. Here we show that online social
interactions during a massive voting event can be used to build an accurate map
of real-world political parties and electoral ranks. We provide evidence that
information flow and collective attention are often driven by a special class
of highly influential users, that we name "augmented humans", who exploit
thousands of automated agents, also known as bots, for enhancing their online
influence. We show that augmented humans generate deep information cascades, to
the same extent of news media and other broadcasters, while they uniformly
infiltrate across the full range of identified groups. Digital augmentation
represents the cyber-physical counterpart of the human desire to acquire power
within social systems.Comment: 11 page
Modeling and Analysis of HetNets with mm-Wave Multi-RAT Small Cells Deployed Along Roads
We characterize a multi tier network with classical macro cells, and multi
radio access technology (RAT) small cells, which are able to operate in
microwave and millimeter-wave (mm-wave) bands. The small cells are assumed to
be deployed along roads modeled as a Poisson line process. This
characterization is more realistic as compared to the classical Poisson point
processes typically used in literature. In this context, we derive the
association and RAT selection probabilities of the typical user under various
system parameters such as the small cell deployment density and mm-wave antenna
gain, and with varying street densities. Finally, we calculate the signal to
interference plus noise ratio (SINR) coverage probability for the typical user
considering a tractable dominant interference based model for mm-wave
interference. Our analysis reveals the need of deploying more small cells per
street in cities with more streets to maintain coverage, and highlights that
mm-wave RAT in small cells can help to improve the SINR performance of the
users.Comment: A 7-page version is submitted to IEEE GLOBECOM 201
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