Bounded-Angle Spanning Tree: Modeling Networks with Angular Constraints

  • Rom Aschner
  • Matthew J. Katz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8573)

Abstract

We introduce a new structure for a set of points in the plane and an angle α, which is similar in flavor to a bounded-degree MST. We name this structure α-MST. Let P be a set of points in the plane and let 0 < α ≤ 2π be an angle. An α-ST of P is a spanning tree of the complete Euclidean graph induced by P, with the additional property that for each point p ∈ P, the smallest angle around p containing all the edges adjacent to p is at most α. An α-MST of P is then an α-ST of P of minimum weight. For α < π/3, an α-ST does not always exist, and, for α ≥ π/3, it always exists [1,2,9]. In this paper, we study the problem of computing an α-MST for several common values of α.

Motivated by wireless networks, we formulate the problem in terms of directional antennas. With each point p ∈ P, we associate a wedge ∧ p of angle α and apex p. The goal is to assign an orientation and a radius r p to each wedge ∧ p, such that the resulting graph is connected and its MST is an α-MST. (We draw an edge between p and q if p ∈ ∧ q, q ∈ ∧ p, and |pq| ≤ r p , r q .) Unsurprisingly, the problem of computing an α-MST is NP-hard, at least for α = π and α = 2π/3. We present constant-factor approximation algorithms for α = π/2, 2π/3, π.

One of our major results is a surprising theorem for α = 2π/3, which, besides being interesting from a geometric point of view, has important applications. For example, the theorem guarantees that given any set P of 3n points in the plane and any partitioning of the points into n triplets, one can orient the wedges of each triplet independently, such that the graph induced by P is connected. We apply the theorem to the antenna conversion problem.

Keywords

Span Tree Hamiltonian Cycle Directional Antenna Communication Graph Unit Disk Graph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Rom Aschner
    • 1
  • Matthew J. Katz
    • 1
  1. 1.Department of Computer ScienceBen-Gurion UniversityIsrael

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