32,291 research outputs found
Distributed boundary tracking using alpha and Delaunay-Cech shapes
For a given point set in a plane, we develop a distributed algorithm to
compute the shape of . shapes are well known geometric
objects which generalize the idea of a convex hull, and provide a good
definition for the shape of . We assume that the distances between pairs of
points which are closer than a certain distance are provided, and we show
constructively that this information is sufficient to compute the alpha shapes
for a range of parameters, where the range depends on .
Such distributed algorithms are very useful in domains such as sensor
networks, where each point represents a sensing node, the location of which is
not necessarily known.
We also introduce a new geometric object called the Delaunay-\v{C}ech shape,
which is geometrically more appropriate than an shape for some cases,
and show that it is topologically equivalent to shapes
Lifetime Improvement in Wireless Sensor Networks via Collaborative Beamforming and Cooperative Transmission
Collaborative beamforming (CB) and cooperative transmission (CT) have
recently emerged as communication techniques that can make effective use of
collaborative/cooperative nodes to create a virtual
multiple-input/multiple-output (MIMO) system. Extending the lifetime of
networks composed of battery-operated nodes is a key issue in the design and
operation of wireless sensor networks. This paper considers the effects on
network lifetime of allowing closely located nodes to use CB/CT to reduce the
load or even to avoid packet-forwarding requests to nodes that have critical
battery life. First, the effectiveness of CB/CT in improving the signal
strength at a faraway destination using energy in nearby nodes is studied.
Then, the performance improvement obtained by this technique is analyzed for a
special 2D disk case. Further, for general networks in which
information-generation rates are fixed, a new routing problem is formulated as
a linear programming problem, while for other general networks, the cost for
routing is dynamically adjusted according to the amount of energy remaining and
the effectiveness of CB/CT. From the analysis and the simulation results, it is
seen that the proposed method can reduce the payloads of energy-depleting nodes
by about 90% in the special case network considered and improve the lifetimes
of general networks by about 10%, compared with existing techniques.Comment: Invited paper to appear in the IEE Proceedings: Microwaves, Antennas
and Propagation, Special Issue on Antenna Systems and Propagation for Future
Wireless Communication
Distributed Dominating Sets on Grids
This paper presents a distributed algorithm for finding near optimal
dominating sets on grids. The basis for this algorithm is an existing
centralized algorithm that constructs dominating sets on grids. The size of the
dominating set provided by this centralized algorithm is upper-bounded by
for grids and its difference
from the optimal domination number of the grid is upper-bounded by five. Both
the centralized and distributed algorithms are generalized for the -distance
dominating set problem, where all grid vertices are within distance of the
vertices in the dominating set.Comment: 10 pages, 9 figures, accepted in ACC 201
Parallelized Particle and Gaussian Sum Particle Filters for Large Scale Freeway Traffic Systems
Large scale traffic systems require techniques able to: 1) deal with high amounts of data and heterogenous data coming from different types of sensors, 2) provide robustness in the presence of sparse sensor data, 3) incorporate different models that can deal with various traffic regimes, 4) cope with multimodal conditional probability density functions for the states. Often centralized architectures face challenges due to high communication demands. This paper develops new estimation techniques able to cope with these problems of large traffic network systems. These are Parallelized Particle Filters (PPFs) and a Parallelized Gaussian Sum Particle Filter (PGSPF) that are suitable for on-line traffic management. We show how complex probability density functions of the high dimensional trafc state can be decomposed into functions with simpler forms and the whole estimation problem solved in an efcient way. The proposed approach is general, with limited interactions which reduces the computational time and provides high estimation accuracy. The efciency of the PPFs and PGSPFs is evaluated in terms of accuracy, complexity and communication demands and compared with the case where all processing is centralized
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