Approximation Algorithms for Directed Weighted Spanners

IF 1.3 4区 物理与天体物理 Q4 PHYSICS, APPLIED Spin Pub Date : 2023-07-06 DOI:10.48550/arXiv.2307.02774
Elena Grigorescu, Nithish Kumar, Young-San Lin
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引用次数: 0

Abstract

In the pairwise weighted spanner problem, the input consists of an $n$-vertex-directed graph, where each edge is assigned a cost and a length. Given $k$ vertex pairs and a distance constraint for each pair, the goal is to find a minimum-cost subgraph in which the distance constraints are satisfied. This formulation captures many well-studied connectivity problems, including spanners, distance preservers, and Steiner forests. In the offline setting, we show: 1. An $\tilde{O}(n^{4/5 + \epsilon})$-approximation algorithm for pairwise weighted spanners. When the edges have unit costs and lengths, the best previous algorithm gives an $\tilde{O}(n^{3/5 + \epsilon})$-approximation, due to Chlamt\'a\v{c}, Dinitz, Kortsarz, and Laekhanukit (TALG, 2020). 2. An $\tilde{O}(n^{1/2+\epsilon})$-approximation algorithm for all-pair weighted distance preservers. When the edges have unit costs and arbitrary lengths, the best previous algorithm gives an $\tilde{O}(n^{1/2})$-approximation for all-pair spanners, due to Berman, Bhattacharyya, Makarychev, Raskhodnikova, and Yaroslavtsev (Information and Computation, 2013). In the online setting, we show: 1. An $\tilde{O}(k^{1/2 + \epsilon})$-competitive algorithm for pairwise weighted spanners. The state-of-the-art results are $\tilde{O}(n^{4/5})$-competitive when edges have unit costs and arbitrary lengths, and $\min\{\tilde{O}(k^{1/2 + \epsilon}), \tilde{O}(n^{2/3 + \epsilon})\}$-competitive when edges have unit costs and lengths, due to Grigorescu, Lin, and Quanrud (APPROX, 2021). 2. An $\tilde{O}(k^{\epsilon})$-competitive algorithm for single-source weighted spanners. Without distance constraints, this problem is equivalent to the directed Steiner tree problem. The best previous algorithm for online directed Steiner trees is $\tilde{O}(k^{\epsilon})$-competitive, due to Chakrabarty, Ene, Krishnaswamy, and Panigrahi (SICOMP, 2018).
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有向加权扳手的近似算法
在两两加权扳手问题中,输入由一个$n$ -顶点定向图组成,其中每条边被分配一个代价和一个长度。给定$k$顶点对和每个顶点对的距离约束,目标是找到满足距离约束的最小代价子图。这个公式抓住了许多研究得很好的连通性问题,包括扳手、距离保存器和斯坦纳森林。在离线设置中,我们显示:1。成对加权扳手的$\tilde{O}(n^{4/5 + \epsilon})$ -近似算法。当边缘具有单位成本和长度时,由于chlamt \v{c}, Dinitz, Kortsarz和Laekhanukit (TALG, 2020),先前最好的算法给出了$\tilde{O}(n^{3/5 + \epsilon})$ -近似。2. 全对加权距离守恒子的$\tilde{O}(n^{1/2+\epsilon})$逼近算法。当边具有单位成本和任意长度时,由于Berman, Bhattacharyya, Makarychev, Raskhodnikova和Yaroslavtsev(信息与计算,2013),先前最好的算法给出了全对扳手的$\tilde{O}(n^{1/2})$ -近似。在在线设置中,我们显示:1。成对加权扳手的$\tilde{O}(k^{1/2 + \epsilon})$竞争算法。根据grigrescu、Lin和Quanrud (APPROX, 2021)的研究,当边具有单位成本和任意长度时,最新的结果是$\tilde{O}(n^{4/5})$ -竞争的,当边具有单位成本和长度时,结果是$\min\{\tilde{O}(k^{1/2 + \epsilon}), \tilde{O}(n^{2/3 + \epsilon})\}$ -竞争的。2. 单源加权扳手的$\tilde{O}(k^{\epsilon})$竞争算法。在没有距离约束的情况下,这个问题等价于有向斯坦纳树问题。由于Chakrabarty, Ene, Krishnaswamy和Panigrahi (SICOMP, 2018),先前在线定向斯坦纳树的最佳算法是$\tilde{O}(k^{\epsilon})$ -竞争算法。
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来源期刊
Spin
Spin Materials Science-Electronic, Optical and Magnetic Materials
CiteScore
2.10
自引率
11.10%
发文量
34
期刊介绍: Spin electronics encompasses a multidisciplinary research effort involving magnetism, semiconductor electronics, materials science, chemistry and biology. SPIN aims to provide a forum for the presentation of research and review articles of interest to all researchers in the field. The scope of the journal includes (but is not necessarily limited to) the following topics: *Materials: -Metals -Heusler compounds -Complex oxides: antiferromagnetic, ferromagnetic -Dilute magnetic semiconductors -Dilute magnetic oxides -High performance and emerging magnetic materials *Semiconductor electronics *Nanodevices: -Fabrication -Characterization *Spin injection *Spin transport *Spin transfer torque *Spin torque oscillators *Electrical control of magnetic properties *Organic spintronics *Optical phenomena and optoelectronic spin manipulation *Applications and devices: -Novel memories and logic devices -Lab-on-a-chip -Others *Fundamental and interdisciplinary studies: -Spin in low dimensional system -Spin in medical sciences -Spin in other fields -Computational materials discovery
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