TY - JOUR
T1 - Parallel algorithms for the edge-coloring and edge-coloring update problems
AU - Liang, Weifa
AU - Shen, Xiaojun
AU - Hu, Qing
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 1996/1/10
Y1 - 1996/1/10
N2 - Let G(V, E) be a simple undirected graph with a maximum vertex degree Δ(G) (or Δ 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 X'(G) (called the chromatic index). For a simple graph G, it is known that Δ ≤ X'(G) ≤ Δ + 1. This paper studies two edge-coloring problems. The first problem is to perform edge-coloring for an existing edge-colored graph G with Δ + 1 colors stemming from the addition of a new vertex into G. The proposed parallel algorithm for this problem runs in O(Δ3/2 log3 Δ + Δ log n) time using O(max{nΔ, Δ3}) processors. The second problem is to color the edges of a given uncolored graph G with Δ + 1 colors. For this problem, our first parallel algorithm requires O(Δ5.5 log3 Δ log n + Δ5 log4 n) time and O(max{n2Δ, nΔ3}) 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(Δ6 log4 n) time and O(n2Δ) 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(Δ4.5 log3 Δ log n + Δ4 log4 n) time and O(max{n2, nΔ3}) processors. Finally, we present our third algorithm by incorporating the second algorithm as a subroutine. This algorithm requires O(Δ3.5 log3 Δ log n + Δ3 log4 n) time and O(max{n2 log Δ, nΔ3}) processors, which improves, by an O(Δ2.5) factor in time, on Karloff and Shmoys' algorithm. All of these algorithms run in the COMMON CRCW PRAM model. © 1996 Academic Press, Inc.
AB - Let G(V, E) be a simple undirected graph with a maximum vertex degree Δ(G) (or Δ 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 X'(G) (called the chromatic index). For a simple graph G, it is known that Δ ≤ X'(G) ≤ Δ + 1. This paper studies two edge-coloring problems. The first problem is to perform edge-coloring for an existing edge-colored graph G with Δ + 1 colors stemming from the addition of a new vertex into G. The proposed parallel algorithm for this problem runs in O(Δ3/2 log3 Δ + Δ log n) time using O(max{nΔ, Δ3}) processors. The second problem is to color the edges of a given uncolored graph G with Δ + 1 colors. For this problem, our first parallel algorithm requires O(Δ5.5 log3 Δ log n + Δ5 log4 n) time and O(max{n2Δ, nΔ3}) 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(Δ6 log4 n) time and O(n2Δ) 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(Δ4.5 log3 Δ log n + Δ4 log4 n) time and O(max{n2, nΔ3}) processors. Finally, we present our third algorithm by incorporating the second algorithm as a subroutine. This algorithm requires O(Δ3.5 log3 Δ log n + Δ3 log4 n) time and O(max{n2 log Δ, nΔ3}) processors, which improves, by an O(Δ2.5) factor in time, on Karloff and Shmoys' algorithm. All of these algorithms run in the COMMON CRCW PRAM model. © 1996 Academic Press, Inc.
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U2 - 10.1006/jpdc.1996.0005
DO - 10.1006/jpdc.1996.0005
M3 - RGC 21 - Publication in refereed journal
SN - 0743-7315
VL - 32
SP - 66
EP - 73
JO - Journal of Parallel and Distributed Computing
JF - Journal of Parallel and Distributed Computing
IS - 1
ER -