scholarly journals Deterministic Distributed (Delta + o(Delta))-Edge-Coloring, and Vertex-Coloring of Graphs with Bounded Diversity

Author(s):  
Leonid Barenboim ◽  
Michael Elkin ◽  
Tzalik Maimon
2022 ◽  
Vol 69 (1) ◽  
pp. 1-26
Author(s):  
Leonid Barenboim ◽  
Michael Elkin ◽  
Uri Goldenberg

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.


Author(s):  
Shing-Tsaan Huang ◽  
Chi-Hung Tzeng ◽  
Jehn-Ruey Jiang

The concept of self-stabilization in distributed systems was introduced by Dijkstra in 1974. A system is said to be self-stabilizing if (1) it can converge in finite time to a legitimate state from any initial state, and (2) when it is in a legitimate state, it remains so henceforth. That is, a self-stabilizing system guarantees to converge to a legitimate state in finite time no matter what initial state it may start with; or, it can recover from transient faults automatically without any outside intervention. This chapter first introduces the self-stabilization concept in distributed computing. Next, it discusses the coloring problem on graphs and its applications in distributed computing. Then, it introduces three self-stabilizing algorithms. The first two are for vertex coloring and edge coloring on planar graphs, respectively. The last one is for edge coloring on bipartite graphs.


Author(s):  
Faraz Dadgostari ◽  
Mahtab Hosseininia

In this chapter a particular type of graph labeling, called graph coloring, is introduced and discussed. In the first part, the simple type of coloring, vertex coloring, is focused. Thus, concerning vertex coloring, some terms and definitions are introduced. Next, some theorems and applying those theorems, some coloring algorithms and applications are introduced. At last, some helpful concepts such as critical graphs, list coloring, and vertex decomposition are presented and discussed. In the second section, edge coloring is focused. Thus, concerning edge coloring, some terms and definitions are described, some important information about edge chromatic number and edge list coloring is presented, and applying them, classification of graphs using the coloring approach is summarized. At last some helpful concepts such as edge list coloring and edge decomposition are illustrated and discussed.


2020 ◽  
Vol 62 (5-6) ◽  
pp. 271-278
Author(s):  
Yannic Maus

AbstractMany modern systems are built on top of large-scale networks like the Internet. This article provides an overview of a dissertation [29] that addresses the complexity of classic graph problems like the vertex coloring problem in such networks. It has been known for a long time that randomization helps significantly in solving many of these problems, whereas the best known deterministic algorithms have been exponentially slower. In the first part of the dissertation we use a complexity theoretic approach to show that several problems are complete in the following sense: An efficient deterministic algorithm for any complete problem would imply an efficient algorithm for all problems that can be solved efficiently with a randomized algorithm. Among the complete problems is a rudimentary looking graph coloring problem that can be solved by a randomized algorithm without any communication. In further parts of the dissertation we develop efficient distributed algorithms for several problems where the most important problems are distributed versions of integer linear programs, the vertex coloring problem and the edge coloring problem. We also prove a lower bound on the runtime of any deterministic algorithm that solves the vertex coloring problem in a weak variant of the standard model of the area.


2021 ◽  
pp. 16-27
Author(s):  
Aparna V. ◽  
◽  
Mohanapriya N. ◽  
Broumi Said ◽  
◽  
...  

The notion of neutrosophic sets facilitates the analysis of values that are unclear or indeterminate. In this paper, we discuss the single-valued neutrosophic R-dynamic vertex coloring of the Cartesian product of SVNG’sand join of SVG's. Further, we have described the concept of single-valued neutrosophic R-dynamic edge coloring and provided some examples and theorems.


2017 ◽  
Vol 9 (1) ◽  
pp. 37
Author(s):  
Siti Khabibah

This paper discuss about Sierpinski star graph , which its construction based on the Sierpinski triangle. Vertex set of Sierpinski star graph  is a set of all triangles in Sierpinski triangle; and the edge set of Sierpinski star graph is a set of  all  sides that are joint edges of  two triangles on Sierpinski triangle. From the vertex and edge coloring of Sierpinski star graph, it is found that the chromatic number on vertex coloring of graph  is 1 for n = 1 and 2 for ; while the chromatic number on edge coloring of graf    is 0 for n = 1 and  for


10.37236/1669 ◽  
2002 ◽  
Vol 9 (1) ◽  
Author(s):  
Garth Isaak

A graph is $f$-choosable if for every collection of lists with list sizes specified by $f$ there is a proper coloring using colors from the lists. The sum choice number is the minimum over all choosable functions $f$ of the sum of the sizes in $f$. We show that the sum choice number of a $2 \times n$ array (equivalent to list edge coloring $K_{2,n}$ and to list vertex coloring the cartesian product $K_2 \square K_n$) is $n^2 + \lceil 5n/3 \rceil$.


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