Affiliation:
1. Open University of Israel, Raanana
2. Ben-Gurion University of the Negev, Beer-Sheva
Abstract
We consider graph coloring and related problems in the distributed message-passing model.
Locally-iterative algorithms
are especially important in this setting. These are algorithms in which each vertex decides about its next color only as a function of the current colors in its
1-hop-neighborhood
. In STOC’93 Szegedy and Vishwanathan showed that any locally-iterative Δ + 1-coloring algorithm requires Ω (Δ log Δ + log
*
n
) rounds, unless there exists “a very special type of coloring that can be very efficiently reduced” [
44
]. No such special coloring has been found since then. This led researchers to believe that Szegedy-Vishwanathan barrier is an inherent limitation for locally-iterative algorithms and to explore other approaches to the coloring problem [
2
,
3
,
19
,
32
]. The latter gave rise to faster algorithms, but their heavy machinery that is of non-locally-iterative nature made them far less suitable to various settings. In this article, we obtain the aforementioned special type of coloring. Specifically, we devise a locally-iterative Δ + 1-coloring algorithm with running time
O
(Δ + log
*
n
), i.e.,
below
Szegedy-Vishwanathan barrier. This demonstrates that this barrier is not an inherent limitation for locally-iterative algorithms. As a result, we also achieve significant improvements for dynamic, self-stabilizing, and bandwidth-restricted settings. This includes the following results:
We obtain self-stabilizing distributed algorithms for Δ + 1-vertex-coloring, (2Δ - 1)-edge-coloring, maximal independent set, and maximal matching with
O
(Δ + log
*
n
) time. This significantly improves previously known results that have
O(n)
or larger running times [
23
].
We devise a (2Δ - 1)-edge-coloring algorithm in the CONGEST model with
O
(Δ + log
*
n
) time and
O
(Δ)-edge-coloring in the Bit-Round model with
O
(Δ + log
n
) time. The factors of log
*
n
and log
n
are unavoidable in the CONGEST and Bit-Round models, respectively. Previously known algorithms had superlinear dependency on Δ for (2Δ - 1)-edge-coloring in these models.
We obtain an arbdefective coloring algorithm with running time
O
(√ Δ + log
*
n
). Such a coloring is not necessarily proper, but has certain helpful properties. We employ it to compute a proper (1 + ε)Δ-coloring within
O
(√ Δ + log
*
n
) time and Δ + 1-coloring within
O
(√ Δ log Δ log
*
Δ + log
*
n
) time. This improves the recent state-of-the-art bounds of Barenboim from PODC’15 [
2
] and Fraigniaud et al. from FOCS’16 [
19
] by polylogarithmic factors.
Our algorithms are applicable to the SET-LOCAL model [
25
] (also known as the weak LOCAL model). In this model a relatively strong lower bound of Ω (Δ
1/3
) is known for Δ + 1-coloring. However, most of the coloring algorithms do not work in this model. (In Reference [
25
] only Linial’s
O
(Δ
2
)-time algorithm and Kuhn-Wattenhofer
O
(Δ log Δ)-time algorithms are shown to work in it.) We obtain the first linear-in-Δ Δ + 1-coloring algorithms that work also in this model.
Funder
Israel Science Foundation
Publisher
Association for Computing Machinery (ACM)
Subject
Artificial Intelligence,Hardware and Architecture,Information Systems,Control and Systems Engineering,Software
Reference45 articles.
1. An energy-efficient, self-stabilizing and distributed algorithm for maximal independent set construction in wireless sensor networks
2. Deterministic (Δ + 1)-Coloring in Sublinear (in Δ) Time in Static, Dynamic, and Faulty Networks
3. L. Barenboim and M. Elkin. 2009. Distributed - coloring in linear (in ) time. In Proceedings of the 41st ACM Symposium on Theory of Computing. 111–120.
4. L. Barenboim and M. Elkin. 2010. Deterministic distributed vertex coloring in polylogarithmic time. In Proceedings of the 29th ACM Symposium on Principles of Distributed Computing. 410–419.
5. L. Barenboim and M. Elkin. 2011. Distributed deterministic edge coloring using bounded neighborhood independence. In Proceedings of the 30th ACM Symposium on Principles of Distributed Computing. 129–138.
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