264 research outputs found
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
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
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
Techniques for Enhanced Physical-Layer Security
Information-theoretic security--widely accepted as the strictest notion of
security--relies on channel coding techniques that exploit the inherent
randomness of propagation channels to strengthen the security of communications
systems. Within this paradigm, we explore strategies to improve secure
connectivity in a wireless network. We first consider the intrinsically secure
communications graph (iS-graph), a convenient representation of the links that
can be established with information-theoretic security on a large-scale
network. We then propose and characterize two techniques--sectorized
transmission and eavesdropper neutralization--which are shown to dramatically
enhance the connectivity of the iS-graph.Comment: Pre-print, IEEE Global Telecommunications Conference (GLOBECOM'10),
Miami, FL, Dec. 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
Connectivity, Coverage and Placement in Wireless Sensor Networks
Wireless communication between sensors allows the formation of flexible sensor networks, which can be deployed rapidly over wide or inaccessible areas. However, the need to gather data from all sensors in the network imposes constraints on the distances between sensors. This survey describes the state of the art in techniques for determining the minimum density and optimal locations of relay nodes and ordinary sensors to ensure connectivity, subject to various degrees of uncertainty in the locations of the nodes
Achieving Small World Properties using Bio-Inspired Techniques in Wireless Networks
It is highly desirable and challenging for a wireless ad hoc network to have
self-organization properties in order to achieve network wide characteristics.
Studies have shown that Small World properties, primarily low average path
length and high clustering coefficient, are desired properties for networks in
general. However, due to the spatial nature of the wireless networks, achieving
small world properties remains highly challenging. Studies also show that,
wireless ad hoc networks with small world properties show a degree distribution
that lies between geometric and power law. In this paper, we show that in a
wireless ad hoc network with non-uniform node density with only local
information, we can significantly reduce the average path length and retain the
clustering coefficient. To achieve our goal, our algorithm first identifies
logical regions using Lateral Inhibition technique, then identifies the nodes
that beamform and finally the beam properties using Flocking. We use Lateral
Inhibition and Flocking because they enable us to use local state information
as opposed to other techniques. We support our work with simulation results and
analysis, which show that a reduction of up to 40% can be achieved for a
high-density network. We also show the effect of hopcount used to create
regions on average path length, clustering coefficient and connectivity.Comment: Accepted for publication: Special Issue on Security and Performance
of Networks and Clouds (The Computer Journal
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