16,697 research outputs found
Robotic Wireless Sensor Networks
In this chapter, we present a literature survey of an emerging, cutting-edge,
and multi-disciplinary field of research at the intersection of Robotics and
Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor
Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system
that aims to achieve certain sensing goals while meeting and maintaining
certain communication performance requirements, through cooperative control,
learning and adaptation. While both of the component areas, i.e., Robotics and
WSN, are very well-known and well-explored, there exist a whole set of new
opportunities and research directions at the intersection of these two fields
which are relatively or even completely unexplored. One such example would be
the use of a set of robotic routers to set up a temporary communication path
between a sender and a receiver that uses the controlled mobility to the
advantage of packet routing. We find that there exist only a limited number of
articles to be directly categorized as RWSN related works whereas there exist a
range of articles in the robotics and the WSN literature that are also relevant
to this new field of research. To connect the dots, we first identify the core
problems and research trends related to RWSN such as connectivity,
localization, routing, and robust flow of information. Next, we classify the
existing research on RWSN as well as the relevant state-of-the-arts from
robotics and WSN community according to the problems and trends identified in
the first step. Lastly, we analyze what is missing in the existing literature,
and identify topics that require more research attention in the future
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
Immunization strategies for epidemic processes in time-varying contact networks
Spreading processes represent a very efficient tool to investigate the
structural properties of networks and the relative importance of their
constituents, and have been widely used to this aim in static networks. Here we
consider simple disease spreading processes on empirical time-varying networks
of contacts between individuals, and compare the effect of several immunization
strategies on these processes. An immunization strategy is defined as the
choice of a set of nodes (individuals) who cannot catch nor transmit the
disease. This choice is performed according to a certain ranking of the nodes
of the contact network. We consider various ranking strategies, focusing in
particular on the role of the training window during which the nodes'
properties are measured in the time-varying network: longer training windows
correspond to a larger amount of information collected and could be expected to
result in better performances of the immunization strategies. We find instead
an unexpected saturation in the efficiency of strategies based on nodes'
characteristics when the length of the training window is increased, showing
that a limited amount of information on the contact patterns is sufficient to
design efficient immunization strategies. This finding is balanced by the large
variations of the contact patterns, which strongly alter the importance of
nodes from one period to the next and therefore significantly limit the
efficiency of any strategy based on an importance ranking of nodes. We also
observe that the efficiency of strategies that include an element of randomness
and are based on temporally local information do not perform as well but are
largely independent on the amount of information available
Contrasting Views of Complexity and Their Implications For Network-Centric Infrastructures
There exists a widely recognized need to better understand
and manage complex âsystems of systems,â ranging from
biology, ecology, and medicine to network-centric technologies.
This is motivating the search for universal laws of highly evolved
systems and driving demand for new mathematics and methods
that are consistent, integrative, and predictive. However, the theoretical
frameworks available today are not merely fragmented
but sometimes contradictory and incompatible. We argue that
complexity arises in highly evolved biological and technological
systems primarily to provide mechanisms to create robustness.
However, this complexity itself can be a source of new fragility,
leading to ârobust yet fragileâ tradeoffs in system design. We
focus on the role of robustness and architecture in networked
infrastructures, and we highlight recent advances in the theory
of distributed control driven by network technologies. This view
of complexity in highly organized technological and biological systems
is fundamentally different from the dominant perspective in
the mainstream sciences, which downplays function, constraints,
and tradeoffs, and tends to minimize the role of organization and
design
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