Towards the Locality of Vizing's Theorem
January 02, 2019 Β· Declared Dead Β· π Symposium on the Theory of Computing
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Hsin-Hao Su, Hoa T. Vu
arXiv ID
1901.00479
Category
cs.DS: Data Structures & Algorithms
Cross-listed
cs.DC
Citations
31
Venue
Symposium on the Theory of Computing
Last Checked
3 months ago
Abstract
Vizing showed that it suffices to color the edges of a simple graph using $Ξ+ 1$ colors, where $Ξ$ is the maximum degree of the graph. However, up to this date, no efficient distributed edge-coloring algorithms are known for obtaining such a coloring, even for constant degree graphs. The current algorithms that get closest to this number of colors are the randomized $(Ξ+ \tildeΞ(\sqrtΞ))$-edge-coloring algorithm that runs in $\text{polylog}(n)$ rounds by Chang et al. (SODA '18) and the deterministic $(Ξ+ \text{polylog}(n))$-edge-coloring algorithm that runs in $\text{poly}(Ξ, \log n)$ rounds by Ghaffari et al. (STOC '18). We present two distributed edge-coloring algorithms that run in $\text{poly}(Ξ,\log n)$ rounds. The first algorithm, with randomization, uses only $Ξ+2$ colors. The second algorithm is a deterministic algorithm that uses $Ξ+ O(\log n/ \log \log n)$ colors. Our approach is to reduce the distributed edge-coloring problem into an online, restricted version of balls-into-bins problem. If $\ell$ is the maximum load of the bins, our algorithm uses $Ξ+ 2\ell - 1$ colors. We show how to achieve $\ell = 1$ with randomization and $\ell = O(\log n / \log \log n)$ without randomization.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Data Structures & Algorithms
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Relief-Based Feature Selection: Introduction and Review
R.I.P.
π»
Ghosted
Route Planning in Transportation Networks
R.I.P.
π»
Ghosted
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
R.I.P.
π»
Ghosted
Hierarchical Clustering: Objective Functions and Algorithms
R.I.P.
π»
Ghosted
Graph Isomorphism in Quasipolynomial Time
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Language Models are Few-Shot Learners
R.I.P.
π»
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
π»
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
π»
Ghosted