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Minimum Scan Cover with Angular Transition Costs

Authors Sándor P. Fekete , Linda Kleist , Dominik Krupke

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LIPIcs.SoCG.2020.43.pdf
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Sándor P. Fekete
  • Department of Computer Science, TU Braunschweig, Germany
Linda Kleist
  • Department of Computer Science, TU Braunschweig, Germany
Dominik Krupke
  • Department of Computer Science, TU Braunschweig, Germany

Acknowledgements

We thank Phillip Keldenich, Irina Kostitsyna, Christian Rieck, and Arne Schmidt for helpful algorithmic discourse, Kenny Cheung (NASA) and Christian Schurig (European Space Agency) for joint work on intersatellite communication, and Karl-Heinz Glaßmeier for discussions of astrophysical aspects.

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Sándor P. Fekete, Linda Kleist, and Dominik Krupke. Minimum Scan Cover with Angular Transition Costs. In 36th International Symposium on Computational Geometry (SoCG 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 164, pp. 43:1-43:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020) https://doi.org/10.4230/LIPIcs.SoCG.2020.43

Abstract

We provide a comprehensive study of a natural geometric optimization problem motivated by questions in the context of satellite communication and astrophysics. In the problem Minimum Scan Cover with Angular Costs (msc), we are given a graph G that is embedded in Euclidean space. The edges of G need to be scanned, i.e., probed from both of their vertices. In order to scan their edge, two vertices need to face each other; changing the heading of a vertex takes some time proportional to the corresponding turn angle. Our goal is to minimize the time until all scans are completed, i.e., to compute a schedule of minimum makespan.
We show that msc is closely related to both graph coloring and the minimum (directed and undirected) cut cover problem; in particular, we show that the minimum scan time for instances in 1D and 2D lies in Θ(log χ(G)), while for 3D the minimum scan time is not upper bounded by χ(G). We use this relationship to prove that the existence of a constant-factor approximation implies P=NP, even for one-dimensional instances. In 2D, we show that it is NP-hard to approximate a minimum scan cover within less than a factor of 3/2, even for bipartite graphs; conversely, we present a 9/2-approximation algorithm for this scenario. Generally, we give an O(c)-approximation for k-colored graphs with k ≤ χ(G)^c. For general metric cost functions, we provide approximation algorithms whose performance guarantee depend on the arboricity of the graph.

Subject Classification

ACM Subject Classification
  • Theory of computation → Design and analysis of algorithms
  • Theory of computation → Computational geometry
Keywords
  • Graph scanning
  • graph coloring
  • angular metric
  • complexity
  • approximation
  • scheduling

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