12,309 research outputs found
Temporal connectivity in finite networks with non-uniform measures
Soft Random Geometric Graphs (SRGGs) have been widely applied to various
models including those of wireless sensor, communication, social and neural
networks. SRGGs are constructed by randomly placing nodes in some space and
making pairwise links probabilistically using a connection function that is
system specific and usually decays with distance. In this paper we focus on the
application of SRGGs to wireless communication networks where information is
relayed in a multi hop fashion, although the analysis is more general and can
be applied elsewhere by using different distributions of nodes and/or
connection functions. We adopt a general non-uniform density which can model
the stationary distribution of different mobility models, with the interesting
case being when the density goes to zero along the boundaries. The global
connectivity properties of these non-uniform networks are likely to be
determined by highly isolated nodes, where isolation can be caused by the
spatial distribution or the local geometry (boundaries). We extend the analysis
to temporal-spatial networks where we fix the underlying non-uniform
distribution of points and the dynamics are caused by the temporal variations
in the link set, and explore the probability a node near the corner is isolated
at time . This work allows for insight into how non-uniformity (caused by
mobility) and boundaries impact the connectivity features of temporal-spatial
networks. We provide a simple method for approximating these probabilities for
a range of different connection functions and verify them against simulations.
Boundary nodes are numerically shown to dominate the connectivity properties of
these finite networks with non-uniform measure.Comment: 13 Pages - 4 figure
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
Percolation and Connectivity in the Intrinsically Secure Communications Graph
The ability to exchange secret information is critical to many commercial,
governmental, and military networks. The intrinsically secure communications
graph (iS-graph) is a random graph which describes the connections that can be
securely established over a large-scale network, by exploiting the physical
properties of the wireless medium. This paper aims to characterize the global
properties of the iS-graph in terms of: (i) percolation on the infinite plane,
and (ii) full connectivity on a finite region. First, for the Poisson iS-graph
defined on the infinite plane, the existence of a phase transition is proven,
whereby an unbounded component of connected nodes suddenly arises as the
density of legitimate nodes is increased. This shows that long-range secure
communication is still possible in the presence of eavesdroppers. Second, full
connectivity on a finite region of the Poisson iS-graph is considered. The
exact asymptotic behavior of full connectivity in the limit of a large density
of legitimate nodes is characterized. Then, simple, explicit expressions are
derived in order to closely approximate the probability of full connectivity
for a finite density of legitimate nodes. The results help clarify how the
presence of eavesdroppers can compromise long-range secure communication.Comment: Submitted for journal publicatio
Research on Wireless Multi-hop Networks: Current State and Challenges
Wireless multi-hop networks, in various forms and under various names, are
being increasingly used in military and civilian applications. Studying
connectivity and capacity of these networks is an important problem. The
scaling behavior of connectivity and capacity when the network becomes
sufficiently large is of particular interest. In this position paper, we
briefly overview recent development and discuss research challenges and
opportunities in the area, with a focus on the network connectivity.Comment: invited position paper to International Conference on Computing,
Networking and Communications, Hawaii, USA, 201
Wireless Secrecy in Large-Scale Networks
The ability to exchange secret information is critical to many commercial,
governmental, and military networks. The intrinsically secure communications
graph (iS-graph) is a random graph which describes the connections that can be
securely established over a large-scale network, by exploiting the physical
properties of the wireless medium. This paper provides an overview of the main
properties of this new class of random graphs. We first analyze the local
properties of the iS-graph, namely the degree distributions and their
dependence on fading, target secrecy rate, and eavesdropper collusion. To
mitigate the effect of the eavesdroppers, we propose two techniques that
improve secure connectivity. Then, we analyze the global properties of the
iS-graph, namely percolation on the infinite plane, and full connectivity on a
finite region. These results help clarify how the presence of eavesdroppers can
compromise secure communication in a large-scale network.Comment: To appear: Proc. IEEE Information Theory and Applications Workshop
(ITA'11), San Diego, CA, Feb. 2011, pp. 1-10, Invited Pape
Fundamentals of Large Sensor Networks: Connectivity, Capacity, Clocks and Computation
Sensor networks potentially feature large numbers of nodes that can sense
their environment over time, communicate with each other over a wireless
network, and process information. They differ from data networks in that the
network as a whole may be designed for a specific application. We study the
theoretical foundations of such large scale sensor networks, addressing four
fundamental issues- connectivity, capacity, clocks and function computation.
To begin with, a sensor network must be connected so that information can
indeed be exchanged between nodes. The connectivity graph of an ad-hoc network
is modeled as a random graph and the critical range for asymptotic connectivity
is determined, as well as the critical number of neighbors that a node needs to
connect to. Next, given connectivity, we address the issue of how much data can
be transported over the sensor network. We present fundamental bounds on
capacity under several models, as well as architectural implications for how
wireless communication should be organized.
Temporal information is important both for the applications of sensor
networks as well as their operation.We present fundamental bounds on the
synchronizability of clocks in networks, and also present and analyze
algorithms for clock synchronization. Finally we turn to the issue of gathering
relevant information, that sensor networks are designed to do. One needs to
study optimal strategies for in-network aggregation of data, in order to
reliably compute a composite function of sensor measurements, as well as the
complexity of doing so. We address the issue of how such computation can be
performed efficiently in a sensor network and the algorithms for doing so, for
some classes of functions.Comment: 10 pages, 3 figures, Submitted to the Proceedings of the IEE
Connectivity in Sub-Poisson Networks
We consider a class of point processes (pp), which we call {\em sub-Poisson};
these are pp that can be directionally-convexly () dominated by some
Poisson pp. The order has already been shown useful in comparing various
point process characteristics, including Ripley's and correlation functions as
well as shot-noise fields generated by pp, indicating in particular that
smaller in the order processes exhibit more regularity (less clustering,
less voids) in the repartition of their points. Using these results, in this
paper we study the impact of the ordering of pp on the properties of two
continuum percolation models, which have been proposed in the literature to
address macroscopic connectivity properties of large wireless networks. As the
first main result of this paper, we extend the classical result on the
existence of phase transition in the percolation of the Gilbert's graph (called
also the Boolean model), generated by a homogeneous Poisson pp, to the class of
homogeneous sub-Poisson pp. We also extend a recent result of the same nature
for the SINR graph, to sub-Poisson pp. Finally, as examples we show that the
so-called perturbed lattices are sub-Poisson. More generally, perturbed
lattices provide some spectrum of models that ranges from periodic grids,
usually considered in cellular network context, to Poisson ad-hoc networks, and
to various more clustered pp including some doubly stochastic Poisson ones.Comment: 8 pages, 10 figures, to appear in Proc. of Allerton 2010. For an
extended version see http://hal.inria.fr/inria-00497707 version
Convergence Speed of the Consensus Algorithm with Interference and Sparse Long-Range Connectivity
We analyze the effect of interference on the convergence rate of average
consensus algorithms, which iteratively compute the measurement average by
message passing among nodes. It is usually assumed that these algorithms
converge faster with a greater exchange of information (i.e., by increased
network connectivity) in every iteration. However, when interference is taken
into account, it is no longer clear if the rate of convergence increases with
network connectivity. We study this problem for randomly-placed
consensus-seeking nodes connected through an interference-limited network. We
investigate the following questions: (a) How does the rate of convergence vary
with increasing communication range of each node? and (b) How does this result
change when each node is allowed to communicate with a few selected far-off
nodes? When nodes schedule their transmissions to avoid interference, we show
that the convergence speed scales with , where is the
communication range and is the number of dimensions. This scaling is the
result of two competing effects when increasing : Increased schedule length
for interference-free transmission vs. the speed gain due to improved
connectivity. Hence, although one-dimensional networks can converge faster from
a greater communication range despite increased interference, the two effects
exactly offset one another in two-dimensions. In higher dimensions, increasing
the communication range can actually degrade the rate of convergence. Our
results thus underline the importance of factoring in the effect of
interference in the design of distributed estimation algorithms.Comment: 27 pages, 4 figure
Connectivity of confined 3D Networks with Anisotropically Radiating Nodes
Nodes in ad hoc networks with randomly oriented directional antenna patterns
typically have fewer short links and more long links which can bridge together
otherwise isolated subnetworks. This network feature is known to improve
overall connectivity in 2D random networks operating at low channel path loss.
To this end, we advance recently established results to obtain analytic
expressions for the mean degree of 3D networks for simple but practical
anisotropic gain profiles, including those of patch, dipole and end-fire array
antennas. Our analysis reveals that for homogeneous systems (i.e. neglecting
boundary effects) directional radiation patterns are superior to the isotropic
case only when the path loss exponent is less than the spatial dimension.
Moreover, we establish that ad hoc networks utilizing directional transmit and
isotropic receive antennas (or vice versa) are always sub-optimally connected
regardless of the environment path loss. We extend our analysis to investigate
boundary effects in inhomogeneous systems, and study the geometrical reasons
why directional radiating nodes are at a disadvantage to isotropic ones.
Finally, we discuss multi-directional gain patterns consisting of many equally
spaced lobes which could be used to mitigate boundary effects and improve
overall network connectivity.Comment: 12 pages, 10 figure
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