Towards the Minimization of Global Measures of Congestion Potential for Moving Points

Imagine a collection of entities moving unpredictably at some bounded speed. Information about entity locations can be maintained by queries, at most one per unit of time, between which location uncertainty grows. Our goal is to minimize global measures of potential congestion defined in terms of the intersection graph of their associated uncertainty regions. As a step towards this larger goal, we study the problem of minimizing the total degree of static entities located in $\mathbb R^1$.


slides
keywords: Computational Geometry, Data Imprecision, Online Algorithms

Workshop or Poster (weakly reviewed)

David Kirkpatrick, Ivor van der Hoog, Maarten Lรถffler, Will Evans
Towards the Minimization of Global Measures of Congestion Potential for Moving Points
Proc. 38th European Workshop on Computational Geometry
, 2022

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