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Exploiting Hopsets: Improved Distance Oracles for Graphs of Constant Highway Dimension and Beyond

机译:利用Hopsets:用于恒定公路尺寸及更高尺寸的图形的改进距离Oracle

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For fixed h = 2, we consider the task of adding to a graph G a set of weighted shortcut edges on the same vertex set, such that the length of a shortest h-hop path between any pair of vertices in the augmented graph is exactly the same as the original distance between these vertices in G. A set of shortcut edges with this property is called an exact h-hopset and may be applied in processing distance queries on graph G. In particular, a 2-hopset directly corresponds to a distributed distance oracle known as a hub labeling. In this work, we explore centralized distance oracles based on 3-hopsets and display their advantages in several practical scenarios. In particular, for graphs of constant highway dimension, and more generally for graphs of constant skeleton dimension, we show that 3-hopsets require exponentially fewer shortcuts per node than any previously described distance oracle, and also offer a speedup in query time when compared to simple oracles based on a direct application of 2-hopsets. Finally, we consider the problem of computing minimum-size h-hopset (for any h = 2) for a given graph G, showing a polylogarithmic-factor approximation for the case of unique shortest path graphs. When h=3, for a given bound on the space used by the distance oracle, we provide a construction of hopset achieving polylog approximation both for space and query time compared to the optimal 3-hopset oracle given the space bound.
机译:对于固定的h> = 2,我们考虑在图G上添加同一顶点集上的一组加权快捷边的任务,以使增强图中的任何一对顶点之间的最短h-hop路径的长度为与G中这些顶点之间的原始距离完全相同。具有此属性的一组快捷方式边称为精确的h-hopset,可用于处理图G上的距离查询。特别是,2-hopset直接对应于称为集线器标签的分布式距离预言。在这项工作中,我们探索基于三跳的集中距离预言机,并在几种实际情况中展示它们的优势。特别是,对于高速公路尺寸恒定的图,以及骨架尺寸恒定的图,我们表明,与每个距离预言相比,三跳集每个节点所需的快捷方式数量成指数地减少,并且与简单的预言基于2跳的直接应用。最后,我们考虑为给定图G计算最小尺寸h-hopset(对于任何h> = 2)的问题,这显示了唯一最短路径图情况下的对数因子近似。当h = 3时,对于给定距离Oracle所使用的空间的给定界限,与给定空间界限的最佳3跳Oracle相比,我们提供了一种跳跃集的构造,可实现空间和查询时间的多对数逼近。

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