Parallel algorithms for the edge-coloring and edge-coloring update problems

被引:3
|
作者
Liang, WF [1 ]
Shen, XJ [1 ]
Hu, Q [1 ]
机构
[1] UNIV MISSOURI,COMP SCI TELECOMMUN PROGRAM,KANSAS CITY,MO 64110
关键词
D O I
10.1006/jpdc.1996.0005
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Let G(V, E) be a simple undirected graph with a maximum vertex degree Delta(G) (or Delta for short), /V/ = n and /E/ = m. An edge-coloring of G is an assignment to each edge in G a color such that all edges sharing a common vertex have different colors. The minimum number of colors needed is denoted by chi'(G) (called the chromatic index). For a simple graph G, it is known that Delta less than or equal to chi'(G) less than or equal to Delta + 1. This paper studies two edge-coloring problems. The first problem is to perform edge-coloring for an existing edge-colored graph G with Delta + 1 colors stemming from the addition of a new vertex into G. The proposed parallel algorithm for this problem runs in O(Delta(3/2)log(3) Delta + Delta log n) time using O(max(n Delta, Delta(3))) processors. The second problem is to color the edges of a given uncolored graph G with Delta + 1 colors. For this problem, our first parallel algorithm requires O(Delta(5.5)log(3) Delta log n + Delta(5) log(4) n) time and O(max{n(2) Delta, n Delta(3)}) processors, which is a slight improvement on the algorithm by H. J. Karloff and D. B. Shmoys [J. Algorithms 8 (1987), 39-52]. Their algorithm costs O(Delta(6) log(4) n) time and O(n(2) Delta) processors if we use the fastest known algorithm for finding maximal independent sets by M. Goldberg and T. Spencer [SIAM J. Discrete Math. 2 (1989), 322-328]. Our second algorithm requires O(Delta(4.5)log(3) Delta log n + Delta(4) log(4) n) time and O(max{n(2), n Delta(3)}) processors. Finally, we present our third algorithm by incorporating the second algorithm as a subroutine. This algorithm requires O(Delta(3.5)log(3) Delta log n + Delta(4) log(4) n) time and O(max{n(2) log Delta, n Delta(3)}) processors, which improves, by an O(Delta(2.5)) factor in time, on Karloff and Shmoys' algorithm. All of these algorithms run in the COMMON CRCW PRAM model. (C) 1996 Academic Press, Inc.
引用
收藏
页码:66 / 73
页数:8
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