English

Distributed Distance Sensitivity Oracles

Data Structures and Algorithms 2025-11-14 v4

Abstract

We present results for the distance sensitivity oracle (DSO) problem, where one needs to preprocess a given directed weighted graph G=(V,E)G=(V,E) in order to answer queries about the shortest path distance in GG from vertex ss to vertex tt avoiding edge ee, for any s,tV,eEs,t \in V, e \in E. DSO enables optimal re-routing under a link failure, and can serve as a key component for fault tolerance in a distributed setting. However, no non-trivial results for DSO are known in the distributed CONGEST model. We present DSO algorithms with different tradeoffs between preprocessing and query cost: one that optimizes query response rounds, and another that prioritizes preprocessing rounds. We complement these algorithms with unconditional CONGEST lower bounds for DSO. Our DSO lower bounds build on a lower bound we present for the kk-source shortest paths problem (kk-SSP), which may be of independent interest. Additionally, we present almost-optimal upper and lower bounds for the related all pairs second simple shortest path (2-APSiSP) problem.

Keywords

Cite

@article{arxiv.2411.13728,
  title  = {Distributed Distance Sensitivity Oracles},
  author = {Vignesh Manoharan and Vijaya Ramachandran},
  journal= {arXiv preprint arXiv:2411.13728},
  year   = {2025}
}

Comments

Extended abstract appears in Proc. SIROCCO 2025. This update includes improved n^2 space DSO, and a few additional new results

R2 v1 2026-06-28T20:07:10.905Z