15 research outputs found
Self-organization of Nodes using Bio-Inspired Techniques for Achieving Small World Properties
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.Comment: Accepted to Joint workshop on complex networks and pervasive group
communication (CCNet/PerGroup), in conjunction with IEEE Globecom 201
Self-Organization of Wireless Ad Hoc Networks as Small Worlds Using Long Range Directional Beams
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.Comment: Accepted to Joint workshop on complex networks and pervasive group
communication (CCNet/PerGroup), in conjunction with IEEE Globecom 201
A Self-Organization Framework for Wireless Ad Hoc Networks as Small Worlds
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.Comment: Submitted to IEEE Transactions on Vehicular Technolog
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
Performance evaluation of directional antennas in ZigBee networks under NLOS propagation conditions
Many authors suggest directional antennas to enhance the transmission performance of
ZigBee networks. For line-of-sight propagation, directional antennas can extend the transmission
range or reduce the transmit power. Directional antennas may also reduce interference between
networks operating in the same frequency channel. However, these antennas may not perform
similarly under non-line-of-sight propagation conditions. This work presents a study with ZigBee
modules comparing the performance of a directional antenna with an omnidirectional one. The
measurements were conducted on a university campus for different propagation outdoor environ ments. A deconvolution technique was applied to estimate the received signal as a function of
the azimuth angle. The results demonstrated that the received power followed the gain difference
between antennas only for paths with low attenuation. Considering the same Effective Isotropic
Radiated Power (EIRP), the system with directional antennas started to lose packets at the same
distance as the omnidirectional antennas. The directional antenna did not allow the increase in the
link range compared to the omnidirectional antenna. The power consumption was also measured for
different transmit power levels of the ZigBee radio. The study showed that the control circuits of
directional antennas typically consume more power than omnidirectional antennas operating at a
higher transmit power level.info:eu-repo/semantics/publishedVersio
Target coverage through distributed clustering in directional sensor networks
Maximum target coverage with minimum number of sensor nodes, known as an MCMS problem, is an important problem in directional sensor networks (DSNs). For guaranteed coverage and event reporting, the underlying mechanism must ensure that all targets are covered by the sensors and the resulting network is connected. Existing solutions allow individual sensor nodes to determine the sensing direction for maximum target coverage which produces sensing coverage redundancy and much overhead. Gathering nodes into clusters might provide a better solution to this problem. In this paper, we have designed distributed clustering and target coverage algorithms to address the problem in an energy-efficient way. To the best of our knowledge, this is the first work that exploits cluster heads to determine the active sensing nodes and their directions for solving target coverage problems in DSNs. Our extensive simulation study shows that our system outperforms a number of state-of-the-art approaches