368 research outputs found
The Internet AS-Level Topology: Three Data Sources and One Definitive Metric
We calculate an extensive set of characteristics for Internet AS topologies
extracted from the three data sources most frequently used by the research
community: traceroutes, BGP, and WHOIS. We discover that traceroute and BGP
topologies are similar to one another but differ substantially from the WHOIS
topology. Among the widely considered metrics, we find that the joint degree
distribution appears to fundamentally characterize Internet AS topologies as
well as narrowly define values for other important metrics. We discuss the
interplay between the specifics of the three data collection mechanisms and the
resulting topology views. In particular, we show how the data collection
peculiarities explain differences in the resulting joint degree distributions
of the respective topologies. Finally, we release to the community the input
topology datasets, along with the scripts and output of our calculations. This
supplement should enable researchers to validate their models against real data
and to make more informed selection of topology data sources for their specific
needs.Comment: This paper is a revised journal version of cs.NI/050803
Influence Robustness of Nodes in Multiplex Networks against Attacks
Recent advances have focused mainly on the resilience of the monoplex network
in attacks targeting random nodes or links, as well as the robustness of the
network against cascading attacks. However, very little research has been done
to investigate the robustness of nodes in multiplex networks against targeted
attacks. In this paper, we first propose a new measure, MultiCoreRank, to
calculate the global influence of nodes in a multiplex network. The measure
models the influence propagation on the core lattice of a multiplex network
after the core decomposition. Then, to study how the structural features can
affect the influence robustness of nodes, we compare the dynamics of node
influence on three types of multiplex networks: assortative, neutral, and
disassortative, where the assortativity is measured by the correlation
coefficient of the degrees of nodes across different layers. We found that
assortative networks have higher resilience against attack than neutral and
disassortative networks. The structure of disassortative networks tends to
break down quicker under attack
The Influence of Network Topology on Sound Propagation in Granular Materials
Granular materials, whose features range from the particle scale to the
force-chain scale to the bulk scale, are usually modeled as either particulate
or continuum materials. In contrast with either of these approaches, network
representations are natural for the simultaneous examination of microscopic,
mesoscopic, and macroscopic features. In this paper, we treat granular
materials as spatially-embedded networks in which the nodes (particles) are
connected by weighted edges obtained from contact forces. We test a variety of
network measures for their utility in helping to describe sound propagation in
granular networks and find that network diagnostics can be used to probe
particle-, curve-, domain-, and system-scale structures in granular media. In
particular, diagnostics of meso-scale network structure are reproducible across
experiments, are correlated with sound propagation in this medium, and can be
used to identify potentially interesting size scales. We also demonstrate that
the sensitivity of network diagnostics depends on the phase of sound
propagation. In the injection phase, the signal propagates systemically, as
indicated by correlations with the network diagnostic of global efficiency. In
the scattering phase, however, the signal is better predicted by meso-scale
community structure, suggesting that the acoustic signal scatters over local
geographic neighborhoods. Collectively, our results demonstrate how the force
network of a granular system is imprinted on transmitted waves.Comment: 19 pages, 9 figures, and 3 table
Public transportation in UK viewed as a complex network
In this paper we investigate the topological and spatial features of public
transport networks (PTN) within the UK. Networks investigated include London,
Manchester, West Midlands, Bristol, national rail and coach networks during
2011. Using methods in complex network theory and statistical physics we are
able to discriminate PTNs with respect to their stability; which is the first
of this kind for national networks. Moreover, taking advantage of various
fractal properties we gain useful insights into the serviceable area of
stations. These features can be employed as key performance indicators in aid
of further developing efficient and stable PTNs.Comment: 23 pages, 9 figure
- …