Proceedings of the Twenty-Fifth Annual ACM Symposium on Theory of Computing - STOC '93 1993
DOI: 10.1145/167088.167156
|View full text |Cite
|
Sign up to set email alerts
|

Locality based graph coloring

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

2
85
0

Year Published

1996
1996
2023
2023

Publication Types

Select...
3
3
2

Relationship

0
8

Authors

Journals

citations
Cited by 72 publications
(88 citation statements)
references
References 9 publications
2
85
0
Order By: Relevance
“…This problem is closely related to the MIS problem, and similarly to the latter problem, the coloring problem is one of the most central and most intensively studied problems in Distributed Algorithms [10,11,17,16,24]. The goal of the coloring problem is to assign colors to vertices so that for each edge e, the endpoints of e are assigned distinct colors.…”
Section: Coloringmentioning
confidence: 99%
“…This problem is closely related to the MIS problem, and similarly to the latter problem, the coloring problem is one of the most central and most intensively studied problems in Distributed Algorithms [10,11,17,16,24]. The goal of the coloring problem is to assign colors to vertices so that for each edge e, the endpoints of e are assigned distinct colors.…”
Section: Coloringmentioning
confidence: 99%
“…At implementation level, this means that each node needs to periodically estimate with a sufficient level of confidence which nodes of the network are potential conflicting neighbours. The majority of decentralised schemes require that each serving node needs local knowledge of the local neighbourhood [3][4][5][6], and any attempt to relax this hypothesis comes at the expense of performance, as shown in Section 2.…”
Section: Wireless Communications and Mobile Computingmentioning
confidence: 99%
“…The characterisation of the first time to FK generally depends on the realisation of a sequence of user reports; this means that is a random variable. More precisely, by (6), is a stopping time; see, for example, [27].…”
Section: Definition 1 (Full Knowledge)mentioning
confidence: 99%
“…Linial [27] proved that O(∆ 2 )-coloring can be computed deterministically in O(log * n) time, independent of ∆. Szegedy and Vishwanathan [38] later improved the running time of this algorithm to √ log n) time [32] or O(∆ + log * n) time [8]. Even if the palette size is enlarged to O(∆), the Panconesi-Srinivasan [32] algorithm remains the fastest, when time is expressed as a function of n. However, Barenboim and Elkin [6] gave an O(min{λ log n, λ + log 1+ n})-time algorithm for O(λ)-coloring, and an O(log λ log n)-time algorithm for λ 1+ -coloring.…”
Section: Deterministic Mis the Fastest Deterministic Mis Algorithms Fmentioning
confidence: 99%
“…The coloring algorithms of [27,38] take O(log * β) time steps in H [1,α−1] , each of which can be simulated with α − 1 time steps in H. By Theorem 2.4,…”
Section: Proofmentioning
confidence: 99%