TY - GEN

T1 - Faster Deterministic Worst-Case Fully Dynamic All-Pairs Shortest Paths via Decremental Hop-Restricted Shortest Paths

AU - Chechik, Shiri

AU - Zhang, Tianyi

N1 - Publisher Copyright:
Copyright © 2023 by SIAM.

PY - 2023

Y1 - 2023

N2 - Dynamic all-pairs shortest paths is a well-studied problem in the field of dynamic graph algorithms. More specifically, given a directed weighted graph G = (V, E, ω) on n vertices which undergoes a sequence of vertex or edge updates, the goal is to maintain distances between any pair of vertices in V. In a classical work by [Demetrscu and Italiano, 2004], the authors showed that all-pairs shortest paths can be maintained deterministically in amortized Õ(n2) time1, which is nearly optimal. For worst-case update time guarantees, so far the best randomized algorithm has Õ(n3-1/3) time [Abraham, Chechik, Krinninger, 2017], and the best deterministic algorithm needs Õ(n3-2/7) time [Probst Gutenberg, Wulff-Nilsen, 2020]. We provide a faster deterministic worst-case update time of Õ(n3-20/61) for fully dynamic all-pairs shortest paths. To achieve this improvement, we study a natural variant of this problem where a hop constraint is imposed on shortest paths between vertices; that is, given a parameter h, the h-hop shortest path between any pair of vertices s, t ∈ V is a path from s to t with at most h edges whose total weight is minimized. As a result which might be of independent interest, we give a deterministic algorithm that maintains all-pairs h-hop shortest paths under vertex deletions in total update time Õ(n3h + Kn2h2), where K bounds the total number of vertex deletions.

AB - Dynamic all-pairs shortest paths is a well-studied problem in the field of dynamic graph algorithms. More specifically, given a directed weighted graph G = (V, E, ω) on n vertices which undergoes a sequence of vertex or edge updates, the goal is to maintain distances between any pair of vertices in V. In a classical work by [Demetrscu and Italiano, 2004], the authors showed that all-pairs shortest paths can be maintained deterministically in amortized Õ(n2) time1, which is nearly optimal. For worst-case update time guarantees, so far the best randomized algorithm has Õ(n3-1/3) time [Abraham, Chechik, Krinninger, 2017], and the best deterministic algorithm needs Õ(n3-2/7) time [Probst Gutenberg, Wulff-Nilsen, 2020]. We provide a faster deterministic worst-case update time of Õ(n3-20/61) for fully dynamic all-pairs shortest paths. To achieve this improvement, we study a natural variant of this problem where a hop constraint is imposed on shortest paths between vertices; that is, given a parameter h, the h-hop shortest path between any pair of vertices s, t ∈ V is a path from s to t with at most h edges whose total weight is minimized. As a result which might be of independent interest, we give a deterministic algorithm that maintains all-pairs h-hop shortest paths under vertex deletions in total update time Õ(n3h + Kn2h2), where K bounds the total number of vertex deletions.

UR - http://www.scopus.com/inward/record.url?scp=85150968888&partnerID=8YFLogxK

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AN - SCOPUS:85150968888

T3 - Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms

SP - 87

EP - 99

BT - 34th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2023

PB - Association for Computing Machinery

T2 - 34th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2023

Y2 - 22 January 2023 through 25 January 2023

ER -