48,525 research outputs found
Coverage and Connectivity in Three-Dimensional Networks
Most wireless terrestrial networks are designed based on the assumption that
the nodes are deployed on a two-dimensional (2D) plane. However, this 2D
assumption is not valid in underwater, atmospheric, or space communications. In
fact, recent interest in underwater acoustic ad hoc and sensor networks hints
at the need to understand how to design networks in 3D. Unfortunately, the
design of 3D networks is surprisingly more difficult than the design of 2D
networks. For example, proofs of Kelvin's conjecture and Kepler's conjecture
required centuries of research to achieve breakthroughs, whereas their 2D
counterparts are trivial to solve. In this paper, we consider the coverage and
connectivity issues of 3D networks, where the goal is to find a node placement
strategy with 100% sensing coverage of a 3D space, while minimizing the number
of nodes required for surveillance. Our results indicate that the use of the
Voronoi tessellation of 3D space to create truncated octahedral cells results
in the best strategy. In this truncated octahedron placement strategy, the
transmission range must be at least 1.7889 times the sensing range in order to
maintain connectivity among nodes. If the transmission range is between 1.4142
and 1.7889 times the sensing range, then a hexagonal prism placement strategy
or a rhombic dodecahedron placement strategy should be used. Although the
required number of nodes in the hexagonal prism and the rhombic dodecahedron
placement strategies is the same, this number is 43.25% higher than the number
of nodes required by the truncated octahedron placement strategy. We verify by
simulation that our placement strategies indeed guarantee ubiquitous coverage.
We believe that our approach and our results presented in this paper could be
used for extending the processes of 2D network design to 3D networks.Comment: To appear in ACM Mobicom 200
Extremal Properties of Three Dimensional Sensor Networks with Applications
In this paper, we analyze various critical transmitting/sensing ranges for
connectivity and coverage in three-dimensional sensor networks. As in other
large-scale complex systems, many global parameters of sensor networks undergo
phase transitions: For a given property of the network, there is a critical
threshold, corresponding to the minimum amount of the communication effort or
power expenditure by individual nodes, above (resp. below) which the property
exists with high (resp. a low) probability. For sensor networks, properties of
interest include simple and multiple degrees of connectivity/coverage. First,
we investigate the network topology according to the region of deployment, the
number of deployed sensors and their transmitting/sensing ranges. More
specifically, we consider the following problems: Assume that nodes, each
capable of sensing events within a radius of , are randomly and uniformly
distributed in a 3-dimensional region of volume , how large
must the sensing range be to ensure a given degree of coverage of the region to
monitor? For a given transmission range, what is the minimum (resp. maximum)
degree of the network? What is then the typical hop-diameter of the underlying
network? Next, we show how these results affect algorithmic aspects of the
network by designing specific distributed protocols for sensor networks
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
Evasion Paths in Mobile Sensor Networks
Suppose that ball-shaped sensors wander in a bounded domain. A sensor doesn't
know its location but does know when it overlaps a nearby sensor. We say that
an evasion path exists in this sensor network if a moving intruder can avoid
detection. In "Coordinate-free coverage in sensor networks with controlled
boundaries via homology", Vin deSilva and Robert Ghrist give a necessary
condition, depending only on the time-varying connectivity data of the sensors,
for an evasion path to exist. Using zigzag persistent homology, we provide an
equivalent condition that moreover can be computed in a streaming fashion.
However, no method with time-varying connectivity data as input can give
necessary and sufficient conditions for the existence of an evasion path.
Indeed, we show that the existence of an evasion path depends not only on the
fibrewise homotopy type of the region covered by sensors but also on its
embedding in spacetime. For planar sensors that also measure weak rotation and
distance information, we provide necessary and sufficient conditions for the
existence of an evasion path
- …