In this work, we propose on-line models to design heterogeneous sensor network topologies with small world features. The proposed model takes into account the data communication flow in this kind of network to create network shortcuts toward the sink node in such a way that the communication between the sink and the sensor nodes is optimized. The endpoints of these shortcuts are nodes with more powerful hardware, leading to a heterogeneous sensor network. We evaluate the on-line models and show that they present the same small world features observed in the theoretical models. When the shortcuts are created toward the sink node, with a small number of powerful sensors, the network presents better small world features and interesting tradeoffs between energy and latency in the data communication when compared with the Random Additional Model. We evaluate the resilience of the on-line models considering general and specific failures and, in both cases, the proposed model is more robust and presents a graceful degradation of the network latency, which shows the resilience of those models.
"The DASM topology is created using the shortcut creation algorithm proposed in . The goal of this topology is to reduce the communication latency although the energy consumption is increased because of the communication through the shortcuts (long range communication). "
[Show abstract][Hide abstract] ABSTRACT: In this work we propose a framework based on the small world features to design Heterogeneous Sensor Network (HSN) topologies with QoS. The framework creates three dif-ferent topologies and each topology has its goals related to the latency and energy consumption during data communication. We also propose a routing algorithm that uses the created topologies in order to provide QoS in HSN. Simulation results showed that the three topologies can provide different levels of QoS that can be used in many sensor network applications. We also compare our framework to the literature topology to provide QoS in HSN and our framework presents better tradeoff between energy consumption and latency during data communication.
IEEE Symposium on Computers and Communications; 06/2012
[Show abstract][Hide abstract] 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.
"Despite above mentioned techniques for achieving shortcuts, problems like finding beam direction, beam length and determining the new neighborhood due to change in the beam properties are always associated in wireless networks. Previous researches on beamforming antennas has been concentrated on networks with uniform distribution and high-density – but very few among them talk about non-uniform distribution of nodes. Most of the researches, considering that all nodes beamform – address connectivity very well but do not discuss the impact on small world characteristics. "
[Show abstract][Hide abstract] 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.
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