159 research outputs found
Combinatorial and Geometric Properties of Planar Laman Graphs
Laman graphs naturally arise in structural mechanics and rigidity theory.
Specifically, they characterize minimally rigid planar bar-and-joint systems
which are frequently needed in robotics, as well as in molecular chemistry and
polymer physics. We introduce three new combinatorial structures for planar
Laman graphs: angular structures, angle labelings, and edge labelings. The
latter two structures are related to Schnyder realizers for maximally planar
graphs. We prove that planar Laman graphs are exactly the class of graphs that
have an angular structure that is a tree, called angular tree, and that every
angular tree has a corresponding angle labeling and edge labeling.
Using a combination of these powerful combinatorial structures, we show that
every planar Laman graph has an L-contact representation, that is, planar Laman
graphs are contact graphs of axis-aligned L-shapes. Moreover, we show that
planar Laman graphs and their subgraphs are the only graphs that can be
represented this way.
We present efficient algorithms that compute, for every planar Laman graph G,
an angular tree, angle labeling, edge labeling, and finally an L-contact
representation of G. The overall running time is O(n^2), where n is the number
of vertices of G, and the L-contact representation is realized on the n x n
grid.Comment: 17 pages, 11 figures, SODA 201
Agglomerative Clustering of Growing Squares
We study an agglomerative clustering problem motivated by interactive glyphs
in geo-visualization. Consider a set of disjoint square glyphs on an
interactive map. When the user zooms out, the glyphs grow in size relative to
the map, possibly with different speeds. When two glyphs intersect, we wish to
replace them by a new glyph that captures the information of the intersecting
glyphs.
We present a fully dynamic kinetic data structure that maintains a set of
disjoint growing squares. Our data structure uses
space, supports queries in worst case time, and updates in
amortized time. This leads to an time
algorithm to solve the agglomerative clustering problem. This is a significant
improvement over the current best time algorithms.Comment: 14 pages, 7 figure
A Framework for Algorithm Stability
We say that an algorithm is stable if small changes in the input result in
small changes in the output. This kind of algorithm stability is particularly
relevant when analyzing and visualizing time-varying data. Stability in general
plays an important role in a wide variety of areas, such as numerical analysis,
machine learning, and topology, but is poorly understood in the context of
(combinatorial) algorithms. In this paper we present a framework for analyzing
the stability of algorithms. We focus in particular on the tradeoff between the
stability of an algorithm and the quality of the solution it computes. Our
framework allows for three types of stability analysis with increasing degrees
of complexity: event stability, topological stability, and Lipschitz stability.
We demonstrate the use of our stability framework by applying it to kinetic
Euclidean minimum spanning trees
Area-Universal Rectangular Layouts
A rectangular layout is a partition of a rectangle into a finite set of
interior-disjoint rectangles. Rectangular layouts appear in various
applications: as rectangular cartograms in cartography, as floorplans in
building architecture and VLSI design, and as graph drawings. Often areas are
associated with the rectangles of a rectangular layout and it might hence be
desirable if one rectangular layout can represent several area assignments. A
layout is area-universal if any assignment of areas to rectangles can be
realized by a combinatorially equivalent rectangular layout. We identify a
simple necessary and sufficient condition for a rectangular layout to be
area-universal: a rectangular layout is area-universal if and only if it is
one-sided. More generally, given any rectangular layout L and any assignment of
areas to its regions, we show that there can be at most one layout (up to
horizontal and vertical scaling) which is combinatorially equivalent to L and
achieves a given area assignment. We also investigate similar questions for
perimeter assignments. The adjacency requirements for the rectangles of a
rectangular layout can be specified in various ways, most commonly via the dual
graph of the layout. We show how to find an area-universal layout for a given
set of adjacency requirements whenever such a layout exists.Comment: 19 pages, 16 figure
Optimal Morphs of Planar Orthogonal Drawings
We describe an algorithm that morphs between two planar orthogonal drawings Gamma_I and Gamma_O of a connected graph G, while preserving planarity and orthogonality. Necessarily Gamma_I and Gamma_O share the same combinatorial embedding. Our morph uses a linear number of linear morphs (linear interpolations between two drawings) and preserves linear complexity throughout the process, thereby answering an open question from Biedl et al. [Biedl et al., 2013].
Our algorithm first unifies the two drawings to ensure an equal number of (virtual) bends on each edge. We then interpret bends as vertices which form obstacles for so-called wires: horizontal and vertical lines separating the vertices of Gamma_O. We can find corresponding wires in Gamma_I that share topological properties with the wires in Gamma_O. The structural difference between the two drawings can be captured by the spirality of the wires in Gamma_I, which guides our morph from Gamma_I to Gamma_O
Topological Stability of Kinetic -Centers
We study the -center problem in a kinetic setting: given a set of
continuously moving points in the plane, determine a set of (moving)
disks that cover at every time step, such that the disks are as small as
possible at any point in time. Whereas the optimal solution over time may
exhibit discontinuous changes, many practical applications require the solution
to be stable: the disks must move smoothly over time. Existing results on this
problem require the disks to move with a bounded speed, but this model is very
hard to work with. Hence, the results are limited and offer little theoretical
insight. Instead, we study the topological stability of -centers.
Topological stability was recently introduced and simply requires the solution
to change continuously, but may do so arbitrarily fast. We prove upper and
lower bounds on the ratio between the radii of an optimal but unstable solution
and the radii of a topologically stable solution---the topological stability
ratio---considering various metrics and various optimization criteria. For we provide tight bounds, and for small we can obtain nontrivial
lower and upper bounds. Finally, we provide an algorithm to compute the
topological stability ratio in polynomial time for constant
Non-Crossing Geometric Steiner Arborescences
Motivated by the question of simultaneous embedding of several flow maps, we consider the problem of drawing multiple geometric Steiner arborescences with no crossings in the rectilinear and in the angle-restricted setting. When terminal-to-root paths are allowed to turn freely, we show that two rectilinear Steiner arborescences have a non-crossing drawing if neither tree necessarily completely disconnects the other tree and if the roots of both trees are "free". If the roots are not free, then we can reduce the decision problem to 2SAT. If terminal-to-root paths are allowed to turn only at Steiner points, then it is NP-hard to decide whether multiple rectilinear Steiner arborescences have a non-crossing drawing. The setting of angle-restricted Steiner arborescences is more subtle than the rectilinear case. Our NP-hardness result extends, but testing whether there exists a non-crossing drawing if the roots of both trees are free requires additional conditions to be fulfilled
Stability analysis of kinetic orientation-based shape descriptors
We study three orientation-based shape descriptors on a set of continuously
moving points: the first principal component, the smallest oriented bounding
box and the thinnest strip. Each of these shape descriptors essentially defines
a cost capturing the quality of the descriptor and uses the orientation that
minimizes the cost. This optimal orientation may be very unstable as the points
are moving, which is undesirable in many practical scenarios. If we bound the
speed with which the orientation of the descriptor may change, this may lower
the quality of the resulting shape descriptor. In this paper we study the
trade-off between stability and quality of these shape descriptors. We first
show that there is no stateless algorithm, an algorithm that keeps no state
over time, that both approximates the minimum cost of a shape descriptor and
achieves continuous motion for the shape descriptor. On the other hand, if we
can use the previous state of the shape descriptor to compute the new state, we
can define "chasing" algorithms that attempt to follow the optimal orientation
with bounded speed. We show that, under mild conditions, chasing algorithms
with sufficient bounded speed approximate the optimal cost at all times for
oriented bounding boxes and strips. The analysis of such chasing algorithms is
challenging and has received little attention in literature, hence we believe
that our methods used in this analysis are of independent interest
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