Algorithms and Lower Bounds for Replacement Paths under Multiple Edge Failure
Virginia Vassilevska Williams, Eyob Woldeghebriel, Yinzhan Xu
Abstract
This paper considers a natural fault-tolerant shortest paths problem: for some constant integer f, given a directed weighted graph with no negative cycles and two fixed vertices s and t, compute (either explicitly or implicitly) for every tuple of f edges, the distance from s to t if these edges fail. We call this problem f-Fault Replacement Paths (f FRP).We first present an ) time algorithm for 2FRP in n-vertex directed graphs with arbitrary edge weights and no negative cycles. As 2FRP is a generalization of the well-studied Replacement Paths problem (RP) that asks for the distances between s and t for any single edge failure, 2FRP is at least as hard as RP. Since RP in graphs with arbitrary weights is equivalent in a fine-grained sense to All-Pairs Shortest Paths (APSP) [Vassilevska Williams and Williams FOCS’10, J. ACM’18], 2FRP is at least as hard as APSP, and thus a substantially subcubic time algorithm in the number of vertices for 2FRP would be a breakthrough. Therefore, our algorithm in time is conditionally nearly optimal. Our algorithm immediately implies an time algorithm for the more general f FRP problem, giving the first improvement over the straightforward time algorithm.Then we focus on the restriction of 2FRP to graphs with small integer weights bounded by M in absolute values. We show that similar to has a substantially subcubic time algorithm for small enough M. Using the current best algorithms for rectangular matrix multiplication, we obtain a randomized algorithm that runs in time. This immediately implies an improvement over our time arbitrary weight algorithm for all . We also present a data structure variant of the algorithm that can trade off pre-processing and query time. In addition to the algebraic algorithms, we also give an conditional lower bound for combinatorial 2FRP algorithms in directed unweighted graphs, and more generally, combinatorial lower bounds for the data structure version of .
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