1,720 research outputs found
Spatially-distributed coverage optimization and control with limited-range interactions
This paper presents coordination algorithms for groups of mobile agents
performing deployment and coverage tasks. As an important modeling constraint,
we assume that each mobile agent has a limited sensing/communication radius.
Based on the geometry of Voronoi partitions and proximity graphs, we analyze a
class of aggregate objective functions and propose coverage algorithms in
continuous and discrete time. These algorithms have convergence guarantees and
are spatially distributed with respect to appropriate proximity graphs.
Numerical simulations illustrate the results.Comment: 31 pages, some figures left out because of size limits. Complete
preprint version available at http://motion.csl.uiuc.ed
The Topology of Wireless Communication
In this paper we study the topological properties of wireless communication
maps and their usability in algorithmic design. We consider the SINR model,
which compares the received power of a signal at a receiver against the sum of
strengths of other interfering signals plus background noise. To describe the
behavior of a multi-station network, we use the convenient representation of a
\emph{reception map}. In the SINR model, the resulting \emph{SINR diagram}
partitions the plane into reception zones, one per station, and the
complementary region of the plane where no station can be heard. We consider
the general case where transmission energies are arbitrary (or non-uniform).
Under that setting, the reception zones are not necessarily convex or even
connected. This poses the algorithmic challenge of designing efficient point
location techniques as well as the theoretical challenge of understanding the
geometry of SINR diagrams. We achieve several results in both directions. We
establish a form of weaker convexity in the case where stations are aligned on
a line. In addition, one of our key results concerns the behavior of a
-dimensional map. Specifically, although the -dimensional map might
be highly fractured, drawing the map in one dimension higher "heals" the zones,
which become connected. In addition, as a step toward establishing a weaker
form of convexity for the -dimensional map, we study the interference
function and show that it satisfies the maximum principle. Finally, we turn to
consider algorithmic applications, and propose a new variant of approximate
point location.Comment: 64 pages, appeared in STOC'1
Static Pricing Problems under Mixed Multinomial Logit Demand
Price differentiation is a common strategy for many transport operators. In
this paper, we study a static multiproduct price optimization problem with
demand given by a continuous mixed multinomial logit model. To solve this new
problem, we design an efficient iterative optimization algorithm that
asymptotically converges to the optimal solution. To this end, a linear
optimization (LO) problem is formulated, based on the trust-region approach, to
find a "good" feasible solution and approximate the problem from below. Another
LO problem is designed using piecewise linear relaxations to approximate the
optimization problem from above. Then, we develop a new branching method to
tighten the optimality gap. Numerical experiments show the effectiveness of our
method on a published, non-trivial, parking choice model
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