Deterministic Incremental APSP with Polylogarithmic Update Time and Stretch


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Date

2023-06-02

Publication Type

Conference Paper

ETH Bibliography

yes

Citations

Altmetric

Data

Abstract

We provide the first deterministic data structure that given a weighted undirected graph undergoing edge insertions, processes each update with polylogarithmic amortized update time and answers queries for the distance between any pair of vertices in the current graph with a polylogarithmic approximation in O(loglogn) time. Prior to this work, no data structure was known for partially dynamic graphs, i.e., graphs undergoing either edge insertions or deletions, with less than no(1) update time except for dense graphs, even when allowing randomization against oblivious adversaries or considering only single-source distances.

Publication status

published

Book title

STOC 2023: Proceedings of the 55th Annual ACM Symposium on Theory of Computing

Journal / series

Volume

Pages / Article No.

1173 - 1186

Publisher

Association for Computing Machinery

Event

55th Annual ACM Symposium on Theory of Computing (STOC '23)

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Dynamic algorithms; Shortest paths; Graph algorithms

Organisational unit

09687 - Kyng, Rasmus / Kyng, Rasmus check_circle

Notes

Funding

204787 - Algorithms and complexity for high-accuracy flows and convex optimization (SNF)

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