1,175 research outputs found
Critical Cooperation Range to Improve Spatial Network Robustness
A robust worldwide air-transportation network (WAN) is one that minimizes the
number of stranded passengers under a sequence of airport closures. Building on
top of this realistic example, here we address how spatial network robustness
can profit from cooperation between local actors. We swap a series of links
within a certain distance, a cooperation range, while following typical
constraints of spatially embedded networks. We find that the network robustness
is only improved above a critical cooperation range. Such improvement can be
described in the framework of a continuum transition, where the critical
exponents depend on the spatial correlation of connected nodes. For the WAN we
show that, except for Australia, all continental networks fall into the same
universality class. Practical implications of this result are also discussed
Switch between critical percolation modes in city traffic dynamics
Percolation transition is widely observed in networks ranging from biology to
engineering. While much attention has been paid to network topologies, studies
rarely focus on critical percolation phenomena driven by network dynamics.
Using extensive real data, we study the critical percolation properties in city
traffic dynamics. Our results suggest that two modes of different critical
percolation behaviors are switching in the same network topology under
different traffic dynamics. One mode of city traffic (during nonrush hours or
days off) has similar critical percolation characteristics as small world
networks, while the other mode (during rush hours on working days) tends to
behave as a 2D lattice. This switching behavior can be understood by the fact
that the high-speed urban roads during nonrush hours or days off (that are
congested during rush hours) represent effective long-range connections, like
in small world networks. Our results might be useful for understanding and
improving traffic resilience.Comment: 8 pages, 4 figures, Daqing Li, Ziyou Gao and H. Eugene Stanley are
the corresponding authors ([email protected], [email protected],
[email protected]
Power Grid Network Evolutions for Local Energy Trading
The shift towards an energy Grid dominated by prosumers (consumers and
producers of energy) will inevitably have repercussions on the distribution
infrastructure. Today it is a hierarchical one designed to deliver energy from
large scale facilities to end-users. Tomorrow it will be a capillary
infrastructure at the medium and Low Voltage levels that will support local
energy trading among prosumers. In our previous work, we analyzed the Dutch
Power Grid and made an initial analysis of the economic impact topological
properties have on decentralized energy trading. In this paper, we go one step
further and investigate how different networks topologies and growth models
facilitate the emergence of a decentralized market. In particular, we show how
the connectivity plays an important role in improving the properties of
reliability and path-cost reduction. From the economic point of view, we
estimate how the topological evolutions facilitate local electricity
distribution, taking into account the main cost ingredient required for
increasing network connectivity, i.e., the price of cabling
Limitations and tradeoffs in synchronization of large-scale networks with uncertain links
We study synchronization in scalar nonlinear systems connected over a linear
network with stochastic uncertainty in their interactions. We provide a
sufficient condition for the synchronization of such network systems expressed
in terms of the parameters of the nonlinear scalar dynamics, the second and
largest eigenvalues of the mean interconnection Laplacian, and the variance of
the stochastic uncertainty. The sufficient condition is independent of network
size thereby making it attractive for verification of synchronization in a
large size network. The main contribution of this paper is to provide
analytical characterization for the interplay of roles played by the internal
dynamics of the nonlinear system, network topology, and uncertainty statistics
in network synchronization. We show there exist important tradeoffs between
these various network parameters necessary to achieve synchronization. We show
for nearest neighbor networks with stochastic uncertainty in interactions there
exists an optimal number of neighbors with maximum margin for synchronization.
This proves in the presence of interaction uncertainty, too many connections
among network components is just as harmful for synchronization as the lack of
connection. We provide an analytical formula for the optimal gain required to
achieve maximum synchronization margin thereby allowing us to compare various
complex network topology for their synchronization property
Crowdsourcing the Robin Hood effect in cities
Socioeconomic inequalities in cities are embedded in space and result in
neighborhood effects, whose harmful consequences have proved very hard to
counterbalance efficiently by planning policies alone. Considering
redistribution of money flows as a first step toward improved spatial equity,
we study a bottom-up approach that would rely on a slight evolution of shopping
mobility practices. Building on a database of anonymized credit card
transactions in Madrid and Barcelona, we quantify the mobility effort required
to reach a reference situation where commercial income is evenly shared among
neighborhoods. The redirections of shopping trips preserve key properties of
human mobility, including travel distances. Surprisingly, for both cities only
a small fraction () of trips need to be altered to reach equity
situations, improving even other sustainability indicators. The method could be
implemented in mobile applications that would assist individuals in reshaping
their shopping practices, to promote the spatial redistribution of
opportunities in the city.Comment: 9 pages, 4 figures + Appendi
Where Graph Topology Matters: The Robust Subgraph Problem
Robustness is a critical measure of the resilience of large networked
systems, such as transportation and communication networks. Most prior works
focus on the global robustness of a given graph at large, e.g., by measuring
its overall vulnerability to external attacks or random failures. In this
paper, we turn attention to local robustness and pose a novel problem in the
lines of subgraph mining: given a large graph, how can we find its most robust
local subgraph (RLS)?
We define a robust subgraph as a subset of nodes with high communicability
among them, and formulate the RLS-PROBLEM of finding a subgraph of given size
with maximum robustness in the host graph. Our formulation is related to the
recently proposed general framework for the densest subgraph problem, however
differs from it substantially in that besides the number of edges in the
subgraph, robustness also concerns with the placement of edges, i.e., the
subgraph topology. We show that the RLS-PROBLEM is NP-hard and propose two
heuristic algorithms based on top-down and bottom-up search strategies.
Further, we present modifications of our algorithms to handle three practical
variants of the RLS-PROBLEM. Experiments on synthetic and real-world graphs
demonstrate that we find subgraphs with larger robustness than the densest
subgraphs even at lower densities, suggesting that the existing approaches are
not suitable for the new problem setting.Comment: 13 pages, 10 Figures, 3 Tables, to appear at SDM 2015 (9 pages only
Updating and downdating techniques for optimizing network communicability
The total communicability of a network (or graph) is defined as the sum of
the entries in the exponential of the adjacency matrix of the network, possibly
normalized by the number of nodes. This quantity offers a good measure of how
easily information spreads across the network, and can be useful in the design
of networks having certain desirable properties. The total communicability can
be computed quickly even for large networks using techniques based on the
Lanczos algorithm.
In this work we introduce some heuristics that can be used to add, delete, or
rewire a limited number of edges in a given sparse network so that the modified
network has a large total communicability. To this end, we introduce new edge
centrality measures which can be used to guide in the selection of edges to be
added or removed.
Moreover, we show experimentally that the total communicability provides an
effective and easily computable measure of how "well-connected" a sparse
network is.Comment: 20 pages, 9 pages Supplementary Materia
Comparing the reliability of networks by spectral analysis
We provide a method for the ranking of the reliability of two networks with
the same connectance. Our method is based on the Cheeger constant linking the
topological property of a network with its spectrum. We first analyze a set of
twisted rings with the same connectance and degree distribution, and obtain the
ranking of their reliability using their eigenvalue gaps. The results are
generalized to general networks using the method of rewiring. The success of
our ranking method is verified numerically for the IEEE57, the
Erd\H{o}s-R\'enyi, and the Small-World networks.Comment: 7 pages, 3 figure
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