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تسجيل مستخدم جديدAn Approximation Algorithm for the Euclidean Bottleneck Steiner Tree Problem
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نشر من قبل
Karim Abu-Affash Mohammed
تاريخ النشر
2010
مجال البحث
الهندسة المعلوماتية
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English
تأليف
A. Karim Abu-Affash
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Given two sets of points in the plane, $P$ of $n$ terminals and $S$ of $m$ Steiner points, a Steiner tree of $P$ is a tree spanning all points of $P$ and some (or none or all) points of $S$. A Steiner tree with length of longest edge minimized is called a bottleneck Steiner tree. In this paper, we study the Euclidean bottleneck Steiner tree problem: given two sets, $P$ and $S$, and a positive integer $k le m$, find a bottleneck Steiner tree of $P$ with at most $k$ Steiner points. The problem has application in the design of wireless communication networks. We first show that the problem is NP-hard and cannot be approximated within factor $sqrt{2}$, unless $P=NP$. Then, we present a polynomial-time approximation algorithm with performance ratio 2.
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We study the multi-level Steiner tree problem: a generalization of the Steiner tree problem in graphs where terminals $T$ require varying priority, level, or quality of service. In this problem, we seek to find a minimum cost tree containing edges of
varying rates such that any two terminals $u$, $v$ with priorities $P(u)$, $P(v)$ are connected using edges of rate $min{P(u),P(v)}$ or better. The case where edge costs are proportional to their rate is approximable to within a constant factor of the optimal solution. For the more general case of non-proportional costs, this problem is hard to approximate with ratio $c log log n$, where $n$ is the number of vertices in the graph. A simple greedy algorithm by Charikar et al., however, provides a $min{2(ln |T|+1), ell rho}$-approximation in this setting, where $rho$ is an approximation ratio for a heuristic solver for the Steiner tree problem and $ell$ is the number of priorities or levels (Byrka et al. give a Steiner tree algorithm with $rhoapprox 1.39$, for example). In this paper, we describe a natural generalization to the multi-level case of the classical (single-level) Steiner tree approximation algorithm based on Kruskals minimum spanning tree algorithm. We prove that this algorithm achieves an approximation ratio at least as good as Charikar et al., and experimentally performs better with respect to the optimum solution. We develop an integer linear programming formulation to compute an exact solution for the multi-level Steiner tree problem with non-proportional edge costs and use it to evaluate the performance of our algorithm on both random graphs and multi-level instances derived from SteinLib.
Lightness is a fundamental parameter for Euclidean spanners; it is the ratio of the spanner weight to the weight of the minimum spanning tree of a finite set of points in $mathbb{R}^d$. In a recent breakthrough, Le and Solomon (2019) established the
precise dependencies on $varepsilon>0$ and $din mathbb{N}$ of the minimum lightness of $(1+varepsilon)$-spanners, and observed that additional Steiner points can substantially improve the lightness. Le and Solomon (2020) constructed Steiner $(1+varepsilon)$-spanners of lightness $O(varepsilon^{-1}logDelta)$ in the plane, where $Deltageq Omega(sqrt{n})$ is the emph{spread} of the point set, defined as the ratio between the maximum and minimum distance between a pair of points. They also constructed spanners of lightness $tilde{O}(varepsilon^{-(d+1)/2})$ in dimensions $dgeq 3$. Recently, Bhore and T{o}th (2020) established a lower bound of $Omega(varepsilon^{-d/2})$ for the lightness of Steiner $(1+varepsilon)$-spanners in $mathbb{R}^d$, for $dge 2$. The central open problem in this area is to close the gap between the lower and upper bounds in all dimensions $dgeq 2$. In this work, we show that for every finite set of points in the plane and every $varepsilon>0$, there exists a Euclidean Steiner $(1+varepsilon)$-spanner of lightness $O(varepsilon^{-1})$; this matches the lower bound for $d=2$. We generalize the notion of shallow light trees, which may be of independent interest, and use directional spanners and a modified window partitioning scheme to achieve a tight weight analysis.
Lightness and sparsity are two natural parameters for Euclidean $(1+varepsilon)$-spanners. Classical results show that, when the dimension $din mathbb{N}$ and $varepsilon>0$ are constant, every set $S$ of $n$ points in $d$-space admits an $(1+varepsi
lon)$-spanners with $O(n)$ edges and weight proportional to that of the Euclidean MST of $S$. Tight bounds on the dependence on $varepsilon>0$ for constant $din mathbb{N}$ have been established only recently. Le and Solomon (FOCS 2019) showed that Steiner points can substantially improve the lightness and sparsity of a $(1+varepsilon)$-spanner. They gave upper bounds of $tilde{O}(varepsilon^{-(d+1)/2})$ for the minimum lightness in dimensions $dgeq 3$, and $tilde{O}(varepsilon^{-(d-1))/2})$ for the minimum sparsity in $d$-space for all $dgeq 1$. They obtained lower bounds only in the plane ($d=2$). Le and Solomon (ESA 2020) also constructed Steiner $(1+varepsilon)$-spanners of lightness $O(varepsilon^{-1}logDelta)$ in the plane, where $Deltain Omega(sqrt{n})$ is the emph{spread} of $S$, defined as the ratio between the maximum and minimum distance between a pair of points. In this work, we improve several bounds on the lightness and sparsity of Euclidean Steiner $(1+varepsilon)$-spanners. Using a new geometric analysis, we establish lower bounds of $Omega(varepsilon^{-d/2})$ for the lightness and $Omega(varepsilon^{-(d-1)/2})$ for the sparsity of such spanners in Euclidean $d$-space for all $dgeq 2$. We use the geometric insight from our lower bound analysis to construct Steiner $(1+varepsilon)$-spanners of lightness $O(varepsilon^{-1}log n)$ for $n$ points in Euclidean plane.
Given a graph $G = (V,E)$ and a subset $T subseteq V$ of terminals, a emph{Steiner tree} of $G$ is a tree that spans $T$. In the vertex-weighted Steiner tree (VST) problem, each vertex is assigned a non-negative weight, and the goal is to compute a m
inimum weight Steiner tree of $G$. We study a natural generalization of the VST problem motivated by multi-level graph construction, the emph{vertex-weighted grade-of-service Steiner tree problem} (V-GSST), which can be stated as follows: given a graph $G$ and terminals $T$, where each terminal $v in T$ requires a facility of a minimum grade of service $R(v)in {1,2,ldotsell}$, compute a Steiner tree $G$ by installing facilities on a subset of vertices, such that any two vertices requiring a certain grade of service are connected by a path in $G$ with the minimum grade of service or better. Facilities of higher grade are more costly than facilities of lower grade. Multi-level variants such as this one can be useful in network design problems where vertices may require facilities of varying priority. While similar problems have been studied in the edge-weighted case, they have not been studied as well in the more general vertex-weighted case. We first describe a simple heuristic for the V-GSST problem whose approximation ratio depends on $ell$, the number of grades of service. We then generalize the greedy algorithm of [Klein & Ravi, 1995] to show that the V-GSST problem admits a $(2 ln |T|)$-approximation, where $T$ is the set of terminals requiring some facility. This result is surprising, as it shows that the (seemingly harder) multi-grade problem can be approximated as well as the VST problem, and that the approximation ratio does not depend on the number of grades of service.
In the Priority Steiner Tree (PST) problem, we are given an undirected graph $G=(V,E)$ with a source $s in V$ and terminals $T subseteq V setminus {s}$, where each terminal $v in T$ requires a nonnegative priority $P(v)$. The goal is to compute a min
imum weight Steiner tree containing edges of varying rates such that the path from $s$ to each terminal $v$ consists of edges of rate greater than or equal to $P(v)$. The PST problem with $k$ priorities admits a $min{2 ln |T| + 2, krho}$-approximation [Charikar et al., 2004], and is hard to approximate with ratio $c log log n$ for some constant $c$ [Chuzhoy et al., 2008]. In this paper, we first strengthen the analysis provided by [Charikar et al., 2004] for the $(2 ln |T| + 2)$-approximation to show an approximation ratio of $lceil log_2 |T| rceil + 1 le 1.443 ln |T| + 2$, then provide a very simple, parallelizable algorithm which achieves the same approximation ratio. We then consider a more difficult node-weighted version of the PST problem, and provide a $(2 ln |T|+2)$-approximation using extensions of the spider decomposition by [Klein & Ravi, 1995]. This is the first result for the PST problem in node-weighted graphs. Moreover, the approximation ratios for all above algorithms are tight.
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