1,948 research outputs found
Asymptotic Analysis of Congested Communication Networks
Projet PROMATHThis paper is devoted to the study of a routing problem in telecommunication networks, when the cost function is the average delay. We establish asymptotic expansions for the value function and solutions in the vicinity of a congested nominal problem. The study is strongly related to the one of a partial inverse barrier method for linear programming
Dynamical properties of model communication networks
We study the dynamical properties of a collection of models for communication
processes, characterized by a single parameter representing the relation
between information load of the nodes and its ability to deliver this
information. The critical transition to congestion reported so far occurs only
for . This case is well analyzed for different network topologies. We
focus of the properties of the order parameter, the susceptibility and the time
correlations when approaching the critical point. For no transition to
congestion is observed but it remains a cross-over from a low-density to a
high-density state. For the transition to congestion is discontinuous
and congestion nuclei arise.Comment: 8 pages, 8 figure
Self-generated Self-similar Traffic
Self-similarity in the network traffic has been studied from several aspects:
both at the user side and at the network side there are many sources of the
long range dependence. Recently some dynamical origins are also identified: the
TCP adaptive congestion avoidance algorithm itself can produce chaotic and long
range dependent throughput behavior, if the loss rate is very high. In this
paper we show that there is a close connection between the static and dynamic
origins of self-similarity: parallel TCPs can generate the self-similarity
themselves, they can introduce heavily fluctuations into the background traffic
and produce high effective loss rate causing a long range dependent TCP flow,
however, the dropped packet ratio is low.Comment: 8 pages, 12 Postscript figures, accepted in Nonlinear Phenomena in
Complex System
A minimal model for congestion phenomena on complex networks
We study a minimal model of traffic flows in complex networks, simple enough
to get analytical results, but with a very rich phenomenology, presenting
continuous, discontinuous as well as hybrid phase transitions between a
free-flow phase and a congested phase, critical points and different scaling
behaviors in the system size. It consists of random walkers on a queueing
network with one-range repulsion, where particles can be destroyed only if they
can move. We focus on the dependence on the topology as well as on the level of
traffic control. We are able to obtain transition curves and phase diagrams at
analytical level for the ensemble of uncorrelated networks and numerically for
single instances. We find that traffic control improves global performance,
enlarging the free-flow region in parameter space only in heterogeneous
networks. Traffic control introduces non-linear effects and, beyond a critical
strength, may trigger the appearance of a congested phase in a discontinuous
manner. The model also reproduces the cross-over in the scaling of traffic
fluctuations empirically observed in the Internet, and moreover, a conserved
version can reproduce qualitatively some stylized facts of traffic in
transportation networks
Traffic Analysis in Random Delaunay Tessellations and Other Graphs
In this work we study the degree distribution, the maximum vertex and edge
flow in non-uniform random Delaunay triangulations when geodesic routing is
used. We also investigate the vertex and edge flow in Erd\"os-Renyi random
graphs, geometric random graphs, expanders and random -regular graphs.
Moreover we show that adding a random matching to the original graph can
considerably reduced the maximum vertex flow.Comment: Submitted to the Journal of Discrete Computational Geometr
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