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A nearly optimal oracle for avoiding failed vertices and edges

机译:避免顶点和边失败的最佳预言

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We present an improved oracle for the distance sensitivity problem. The goal is to preprocess a directed graph G = (V,E) with non-negative edge weights to answer queries of the form: what is the length of the shortest path from x to y that does not go through some failed vertex or edge f. The previous best algorithm produces an oracle of size ~O(n2) that has an O(1) query time, and an ~O(n2√m) construction time. It was a randomized Monte Carlo algorithm that worked with high probability. Our oracle also has a constant query time and an ~O(n2) space requirement, but it has an improved construction time of ~O(mn), and it is deterministic. Note that O(1) query, O(n2) space, and O(mn) construction time is also the best known bound (up to logarithmic factors) for the simpler problem of finding all pairs shortest paths in a weighted, directed graph. Thus, barring improved solutions to the all pairs shortest path problem, our oracle is optimal up to logarithmic factors.
机译:我们针对距离敏感度问题提出了一种改进的预言。目标是预处理具有非负边权重的有向图G =(V,E),以回答以下形式的查询:从x到y的最短路径的长度(不经过某个失败的顶点或边)是多少? F。先前的最佳算法会生成一个大小为〜O(n2)的预言机,该预言机具有O(1)查询时间和〜O(n2√m)构造时间。这是一个随机的蒙特卡洛算法,具有很高的概率。我们的预言机还具有恒定的查询时间和〜O(n2)空间要求,但它的构造时间缩短了〜O(mn),并且具有确定性。请注意,O(1)查询,O(n2)空间和O(mn)构造时间也是最简单的问题(最多对数因子),这是在加权有向图中查找所有对最短路径的较简单问题。因此,除非对所有对最短路径问题有改进的解决方案,否则我们的预言家在对数因子方面是最优的。

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