Constant-time Dynamic (Δ +1)-Coloring

Henzinger MH, Peng P. 2022. Constant-time Dynamic (Δ +1)-Coloring. ACM Transactions on Algorithms. 18(2), 16.

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Abstract
We give a fully dynamic (Las-Vegas style) algorithm with constant expected amortized time per update that maintains a proper (Δ +1)-vertex coloring of a graph with maximum degree at most Δ. This improves upon the previous O(log Δ)-time algorithm by Bhattacharya et al. (SODA 2018). Our algorithm uses an approach based on assigning random ranks to vertices and does not need to maintain a hierarchical graph decomposition. We show that our result does not only have optimal running time but is also optimal in the sense that already deciding whether a Δ-coloring exists in a dynamically changing graph with maximum degree at most Δ takes Ω (log n) time per operation.
Publishing Year
Date Published
2022-03-04
Journal Title
ACM Transactions on Algorithms
Acknowledgement
We want to thank an anonymous referee who pointed out a mistake in our conference paper as well as suggesting a fix using an approach in References.
Volume
18
Issue
2
Article Number
16
ISSN
eISSN
IST-REx-ID

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Henzinger MH, Peng P. Constant-time Dynamic (Δ +1)-Coloring. ACM Transactions on Algorithms. 2022;18(2). doi:10.1145/3501403
Henzinger, M. H., & Peng, P. (2022). Constant-time Dynamic (Δ +1)-Coloring. ACM Transactions on Algorithms. Association for Computing Machinery (ACM). https://doi.org/10.1145/3501403
Henzinger, Monika H, and Pan Peng. “Constant-Time Dynamic (Δ +1)-Coloring.” ACM Transactions on Algorithms. Association for Computing Machinery (ACM), 2022. https://doi.org/10.1145/3501403.
M. H. Henzinger and P. Peng, “Constant-time Dynamic (Δ +1)-Coloring,” ACM Transactions on Algorithms, vol. 18, no. 2. Association for Computing Machinery (ACM), 2022.
Henzinger MH, Peng P. 2022. Constant-time Dynamic (Δ +1)-Coloring. ACM Transactions on Algorithms. 18(2), 16.
Henzinger, Monika H., and Pan Peng. “Constant-Time Dynamic (Δ +1)-Coloring.” ACM Transactions on Algorithms, vol. 18, no. 2, 16, Association for Computing Machinery (ACM), 2022, doi:10.1145/3501403.

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