Improved Distance Sensitivity Oracles with Subcubic Preprocessing Time
Hanlin Ren

TL;DR
This paper introduces a new Distance Sensitivity Oracle with improved preprocessing time of approximately O(n^{2.72} M) for directed graphs, achieving constant query time, representing a significant efficiency advancement over previous methods.
Contribution
The paper presents a novel DSO with subcubic preprocessing time and constant query time, improving upon prior work with a more efficient construction algorithm.
Findings
Preprocessing time reduced to ~O(n^{2.72} M) for directed graphs.
Achieves constant query time for shortest path queries with failures.
Improves preprocessing time for undirected graphs to ~O(n^{2.69} M).
Abstract
We consider the problem of building Distance Sensitivity Oracles (DSOs). Given a directed graph with edge weights in , we need to preprocess it into a data structure, and answer the following queries: given vertices and a failed vertex or edge , output the length of the shortest path from to that does not go through . Our main result is a simple DSO with preprocessing time and query time. Moreover, if the input graph is undirected, the preprocessing time can be improved to . The preprocessing algorithm is randomized with correct probability , for a constant that can be made arbitrarily large. Previously, there is a DSO with preprocessing time and query time [Chechik and Cohen, STOC'20]. At the…
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