5 research outputs found
Connectivity in Dense Networks Confined within Right Prisms
We consider the probability that a dense wireless network confined within a
given convex geometry is fully connected. We exploit a recently reported theory
to develop a systematic methodology for analytically characterizing the
connectivity probability when the network resides within a convex right prism,
a polyhedron that accurately models many geometries that can be found in
practice. To maximize practicality and applicability, we adopt a general
point-to-point link model based on outage probability, and present example
analytical and numerical results for a network employing
multiple-input multiple-output (MIMO) maximum ratio combining (MRC) link level
transmission confined within particular bounding geometries. Furthermore, we
provide suggestions for extending the approach detailed herein to more general
convex geometries.Comment: 8 pages, 6 figures. arXiv admin note: text overlap with
arXiv:1201.401
More is less: Connectivity in fractal regions
Ad-hoc networks are often deployed in regions with complicated boundaries. We
show that if the boundary is modeled as a fractal, a network requiring line of
sight connections has the counterintuitive property that increasing the number
of nodes decreases the full connection probability. We characterise this decay
as a stretched exponential involving the fractal dimension of the boundary, and
discuss mitigation strategies. Applications of this study include the analysis
and design of sensor networks operating in rugged terrain (e.g. railway
cuttings), mm-wave networks in industrial settings and
vehicle-to-vehicle/vehicle-to-infrastructure networks in urban environments.Comment: 5 page
Epidemic Spreading in Random Rectangular Networks
The use of network theory to model disease propagation on populations
introduces important elements of reality to the classical epidemiological
models. The use of random geometric graphs (RGG) is one of such network models
that allows for the consideration of spatial properties on disease propagation.
In certain real-world scenarios -like in the analysis of a disease propagating
through plants- the shape of the plots and fields where the host of the disease
is located may play a fundamental role on the propagation dynamics. Here we
consider a generalization of the RGG to account for the variation of the shape
of the plots/fields where the hosts of a disease are allocated. We consider a
disease propagation taking place on the nodes of a random rectangular graph
(RRG) and we consider a lower bound for the epidemic threshold of a
Susceptible-Infected-Susceptible (SIS) or Susceptible-Infected-Recovered (SIR)
model on these networks. Using extensive numerical simulations and based on our
analytical results we conclude that (ceteris paribus) the elongation of the
plot/field in which the nodes are distributed makes the network more resilient
to the propagation of a disease due to the fact that the epidemic threshold
increases with the elongation of the rectangle. These results agree with
accumulated empirical evidence and simulation results about the propagation of
diseases on plants in plots/fields of the same area and different shapes.Comment: Version 4, 13 pages, 6 figures, 44 ref
Spatial networks with wireless applications
Many networks have nodes located in physical space, with links more common
between closely spaced pairs of nodes. For example, the nodes could be wireless
devices and links communication channels in a wireless mesh network. We
describe recent work involving such networks, considering effects due to the
geometry (convex,non-convex, and fractal), node distribution,
distance-dependent link probability, mobility, directivity and interference.Comment: Review article- an amended version with a new title from the origina