A \emph{sparsification} of a given graph $G$ is a sparser graph (typically a subgraph) which aims to approximate or preserve some property of $G$. Examples of sparsifications include but are not limited to spanning trees, Steiner trees, spanners, emulators, and distance preservers. Each vertex has the same priority in all of these problems. However, real-world graphs typically assign different ``priorities'' or ``levels'' to different vertices, in which higher-priority vertices require higher-quality connectivity between them. Multi-priority variants of the Steiner tree problem have been studied in prior literature but this generalization is much less studied for other sparsification problems. In this paper, we define a generalized multi-priority problem and present a rounding-up approach that can be used for a variety of graph sparsifications. Our analysis provides a systematic way to compute approximate solutions to multi-priority variants of a wide range of graph sparsification problems given access to a single-priority subroutine.
翻译:\ emph{ reparisization} 给定的图形$G$ 是一个稀疏的图表(通常是子图), 目的是接近或保存某些G$的属性。 环状图的例子包括但不限于横贯树木、 Steiner 树、 光扇、 模擬器和距离保护器。 每个顶点在所有这些问题中都具有同样的优先地位。 然而, 真实世界的图表通常给不同的顶点分配不同的“ 优先度” 或“ 水平”, 其中, 高优先的顶点要求它们之间有更高质量的连接。 以前的文献已经研究了施泰纳树问题的多优先变体, 但对于其他的环状问题则很少研究这种概括化。 在本文中, 我们定义了一个普遍的多优先度问题, 并提出了一种圆形方法, 可用于各种图质聚变体。 我们的分析提供了系统的方法, 来对一系列图质的细微分点问题的多优先变量进行估计。