Publications (5)0 Total impact
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ABSTRACT: Mobility causes network structures to change. In PSNs where underlying
network structure is changing rapidly, we are interested in studying how
information dissemination can be enhanced in a sparse disconnected network
where nodes lack the global knowledge about the network. We use beamforming to
study the enhancement in the information dissemination process. In order to
identify potential beamformers and nodes to which beams should be directed we
use the concept of stability. We first predict the stability of a node in the
dynamic network using truncated levy walk nature of jump lengths of human
mobility and then use this measure to identify beamforming nodes and the nodes
to which the beams are directed. We also develop our algorithm such that it
does not require any global knowledge about the network and works in a
distributed manner. We also show the effect of various parameters such as
number of sources, number of packets, mobility parameters, antenna parameters,
type of stability used and density of the network on information dissemination
in the network. We validate our findings with three validation model, no
beamforming, beamforming using different stability measure and when no
stability measure is associated but same number of node beamform and the
selection of the beamforming nodes is random. Our simulation results show that
information dissemination can be enhanced using our algorithm over other
models.
10/2012;
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ABSTRACT: Motivated by the benefits of small world networks, we propose a
self-organization framework for wireless ad hoc networks. We investigate the
use of directional beamforming for creating long-range short cuts between
nodes. Using simulation results for randomized beamforming as a guideline, we
identify crucial design issues for algorithm design. Our results show that,
while significant path length reduction is achievable, this is accompanied by
the problem of asymmetric paths between nodes. Subsequently, we propose a
distributed algorithm for small world creation that achieves path length
reduction while maintaining connectivity. We define a new centrality measure
that estimates the structural importance of nodes based on traffic flow in the
network, which is used to identify the optimum nodes for beamforming. We show,
using simulations, that this leads to significant reduction in path length
while maintaining connectivity.
03/2012;
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ABSTRACT: 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.
11/2011;
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ABSTRACT: In an autonomous wireless sensor network, self-organization of the nodes is
essential to achieve network wide characteristics. We believe that connectivity
in wireless autonomous networks can be increased and overall average path
length can be reduced by using beamforming and bio-inspired algorithms. Recent
works on the use of beamforming in wireless networks mostly assume the
knowledge of the network in aggregation to either heterogeneous or hybrid
deployment. We propose that without the global knowledge or the introduction of
any special feature, the average path length can be reduced with the help of
inspirations from the nature and simple interactions between neighboring nodes.
Our algorithm also reduces the number of disconnected components within the
network. Our results show that reduction in the average path length and the
number of disconnected components can be achieved using very simple local rules
and without the full network knowledge.
09/2011;
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ABSTRACT: We study how long range directional beams can be used for self-organization
of a wireless network to exhibit small world properties. Using simulation
results for randomized beamforming as a guideline, we identify crucial design
issues for algorithm design. Subsequently, we propose an algorithm for
deterministic creation of small worlds. We define a new centrality measure that
estimates the structural importance of nodes based on traffic flow in the
network, which is used to identify the optimum nodes for beamforming. This
results in significant reduction in path length while maintaining connectivity.
09/2011;
