English

Dual Failure Resilient BFS Structure

Data Structures and Algorithms 2015-05-05 v1

Abstract

We study {\em breadth-first search (BFS)} spanning trees, and address the problem of designing a sparse {\em fault-tolerant} BFS structure, or {\em FT-BFS } for short, resilient to the failure of up to two edges in the given undirected unweighted graph GG, i.e., a sparse subgraph HH of GG such that subsequent to the failure of up to two edges, the surviving part HH' of HH still contains a BFS spanning tree for (the surviving part of) GG. FT-BFS structures, as well as the related notion of replacement paths, have been studied so far for the restricted case of a single failure. It has been noted widely that when concerning shortest-paths in a variety of contexts, there is a sharp qualitative difference between a single failure and two or more failures. Our main results are as follows. We present an algorithm that for every nn-vertex unweighted undirected graph GG and source node ss constructs a (two edge failure) FT-BFS structure rooted at ss with O(n5/3)O(n^{5/3}) edges. To provide a useful theory of shortest paths avoiding 2 edges failures, we take a principled approach to classifying the arrangement these paths. We believe that the structural analysis provided in this paper may decrease the barrier for understanding the general case of f2f\geq 2 faults and pave the way to the future design of ff-fault resilient structures for f2f \geq 2. We also provide a matching lower bound, which in fact holds for the general case of f1f \geq 1 and multiple sources SVS \subseteq V. It shows that for every f1f\geq 1, and integer 1σn1 \leq \sigma \leq n, there exist nn-vertex graphs with a source set SVS \subseteq V of cardinality σ\sigma for which any FT-BFS structure rooted at each sSs \in S, resilient to up to ff-edge faults has Ω(σ1/(f+1)n21/(f+1))\Omega(\sigma^{1/(f+1)} \cdot n^{2-1/(f+1)}) edges.

Keywords

Cite

@article{arxiv.1505.00692,
  title  = {Dual Failure Resilient BFS Structure},
  author = {Merav Parter},
  journal= {arXiv preprint arXiv:1505.00692},
  year   = {2015}
}
R2 v1 2026-06-22T09:27:44.842Z