Distributed Distance Sensitivity Oracles
Abstract
We present results for the distance sensitivity oracle (DSO) problem, where one needs to preprocess a given directed weighted graph in order to answer queries about the shortest path distance in from vertex to vertex avoiding edge , for any . 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 -source shortest paths problem (-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.
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