TY - GEN

T1 - Graph orientaion to maximize the minmum weighted outdegre

AU - Asahiro, Yuichi

AU - Jansso, Jesper

AU - Miyano, Eiji

AU - Ono, Hirotaka

PY - 2009

Y1 - 2009

N2 - We study a new variant of the graph orientation problem called MAXMINO where the input is an undirected, edge-weighted graph and the objective is to assign a direction to each edge so that the minimum weighted outdegree (taken over all vertices in the resulting directed graph) is maximized. All edge weights are assumed to be positive integers. This problem is closely related to the job scheduling on parallel machines, called the machine covering problem, where its goal is to assign jobs to parallel machines such that each machine is covered as much as possible. First, we prove that MAXMINO is strongly NP-hard and cannot be approximated within a ratio of 2 - ε for any constant ε > 0 in polynomial time unless P-NP, even if all edge weights belong to {1,2}, every vertex has degree at most three, and the input graph is bipartite or planar. Next, we show how to solve MAXMINO exactly in polynomial time for the special case in which all edge weights are equal to 1. This technique gives us a simple polynomial-time Wmax/Wmin-approximation algorithm for MAXMINO where wmax and wmin denote the maximum and minimum weights among all the input edges. Furthermore, we also observe that this approach yields an exact algorithm for the general case of MAXMINO whose running time is polynomial whenever the number of edges having weight larger than wmin is at most logarithmic in the number of vertices. Finally, we show that MAXMINO is solvable in polynomial time if the input is a cactus graph.

AB - We study a new variant of the graph orientation problem called MAXMINO where the input is an undirected, edge-weighted graph and the objective is to assign a direction to each edge so that the minimum weighted outdegree (taken over all vertices in the resulting directed graph) is maximized. All edge weights are assumed to be positive integers. This problem is closely related to the job scheduling on parallel machines, called the machine covering problem, where its goal is to assign jobs to parallel machines such that each machine is covered as much as possible. First, we prove that MAXMINO is strongly NP-hard and cannot be approximated within a ratio of 2 - ε for any constant ε > 0 in polynomial time unless P-NP, even if all edge weights belong to {1,2}, every vertex has degree at most three, and the input graph is bipartite or planar. Next, we show how to solve MAXMINO exactly in polynomial time for the special case in which all edge weights are equal to 1. This technique gives us a simple polynomial-time Wmax/Wmin-approximation algorithm for MAXMINO where wmax and wmin denote the maximum and minimum weights among all the input edges. Furthermore, we also observe that this approach yields an exact algorithm for the general case of MAXMINO whose running time is polynomial whenever the number of edges having weight larger than wmin is at most logarithmic in the number of vertices. Finally, we show that MAXMINO is solvable in polynomial time if the input is a cactus graph.

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U2 - 10.1109/IPDPS.2009.5160872

DO - 10.1109/IPDPS.2009.5160872

M3 - Conference contribution

AN - SCOPUS:70449823954

SN - 9781424437504

T3 - IPDPS 2009 - Proceedings of the 2009 IEEE International Parallel and Distributed Processing Symposium

BT - IPDPS 2009 - Proceedings of the 2009 IEEE International Parallel and Distributed Processing Symposium

T2 - 23rd IEEE International Parallel and Distributed Processing Symposium, IPDPS 2009

Y2 - 23 May 2009 through 29 May 2009

ER -