2,637 research outputs found
Information Spreading in Stationary Markovian Evolving Graphs
Markovian evolving graphs are dynamic-graph models where the links among a
fixed set of nodes change during time according to an arbitrary Markovian rule.
They are extremely general and they can well describe important dynamic-network
scenarios.
We study the speed of information spreading in the "stationary phase" by
analyzing the completion time of the "flooding mechanism". We prove a general
theorem that establishes an upper bound on flooding time in any stationary
Markovian evolving graph in terms of its node-expansion properties.
We apply our theorem in two natural and relevant cases of such dynamic
graphs. "Geometric Markovian evolving graphs" where the Markovian behaviour is
yielded by "n" mobile radio stations, with fixed transmission radius, that
perform independent random walks over a square region of the plane.
"Edge-Markovian evolving graphs" where the probability of existence of any edge
at time "t" depends on the existence (or not) of the same edge at time "t-1".
In both cases, the obtained upper bounds hold "with high probability" and
they are nearly tight. In fact, they turn out to be tight for a large range of
the values of the input parameters. As for geometric Markovian evolving graphs,
our result represents the first analytical upper bound for flooding time on a
class of concrete mobile networks.Comment: 16 page
On the Dynamics of the U.S. Manufacturing Productivity Distribution
In this paper a model of productivity dynamics of manufacturing industries is developed with key features being the absence of optimal decisions and equilibrium coordination, heterogeneity of industries with respect to their innovative ability and cumulativeness of innovations together with the working of spillover effects. From that model the law of motion of the productivity distribution across the industries is derived and nonparametrically estimated using data for U.S. manufacturing industries over the period 1958-96. The conclusion of a substantial role of persistence in the productivity development is sharpened by the application of unit root and stationarity tests for panel data.distribution dynamics, productivity, persistence, panel unit root test
Intertemporal choice and consumption mobility
The theory of intertemporal consumption choice makes sharp predictions about the evolution of the entire distribution of household consumption, not just about its conditional mean. In the paper, we study the empirical transition matrix of consumption using a panel drawn from the Bank of Italy Survey of Household Income and Wealth. We estimate the parameters that minimize the distance between the empirical and the theoretical transition matrix of the consumption distribution. The transition matrix generated by our estimates matches remarkably well the empirical matrix, both in the aggregate and in samples stratified by education. Our estimates strongly reject the consumption insurance model and suggest that households smooth income shocks to a lesser extent than implied by the permanent income hypothesis. Klassifikation: D52, D91, I3
The heterogeneity of inter-contact time distributions: its importance for routing in delay tolerant networks
Prior work on routing in delay tolerant networks (DTNs) has commonly made the
assumption that each pair of nodes shares the same inter-contact time
distribution as every other pair. The main argument in this paper is that
researchers should also be looking at heterogeneous inter-contact time
distributions. We demonstrate the presence of such heterogeneity in the
often-used Dartmouth Wi-Fi data set. We also show that DTN routing can benefit
from knowing these distributions. We first introduce a new stochastic model
focusing on the inter-contact time distributions between all pairs of nodes,
which we validate on real connectivity patterns. We then analytically derive
the mean delivery time for a bundle of information traversing the network for
simple single copy routing schemes. The purpose is to examine the theoretic
impact of heterogeneous inter-contact time distributions. Finally, we show that
we can exploit this user diversity to improve routing performance.Comment: 6 page
A Lightweight Distributed Solution to Content Replication in Mobile Networks
Performance and reliability of content access in mobile networks is
conditioned by the number and location of content replicas deployed at the
network nodes. Facility location theory has been the traditional, centralized
approach to study content replication: computing the number and placement of
replicas in a network can be cast as an uncapacitated facility location
problem. The endeavour of this work is to design a distributed, lightweight
solution to the above joint optimization problem, while taking into account the
network dynamics. In particular, we devise a mechanism that lets nodes share
the burden of storing and providing content, so as to achieve load balancing,
and decide whether to replicate or drop the information so as to adapt to a
dynamic content demand and time-varying topology. We evaluate our mechanism
through simulation, by exploring a wide range of settings and studying
realistic content access mechanisms that go beyond the traditional
assumptionmatching demand points to their closest content replica. Results show
that our mechanism, which uses local measurements only, is: (i) extremely
precise in approximating an optimal solution to content placement and
replication; (ii) robust against network mobility; (iii) flexible in
accommodating various content access patterns, including variation in time and
space of the content demand.Comment: 12 page
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