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Maximum Edge-Disjoint Paths in Planar Graphs with Congestion 2

机译:平面图中拥塞2的最大边缘不相交路径

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We study the maximum edge-disjoint path problem (MEDP) in planar graphs. We are given a set of terminal pairs and wish to find a maximum routable subset of demands. That is, a subset of demands that can be connected by edge-disjoint paths. It is well-known that there is an integrality gap of order square root of the number of nodes for this problem even on a grid-like graph, and hence in planar graphs (Garg et al.). In contrast, Chekuri et al. show that for planar graphs, if LP is the optimal solution to the natural linear programming relaxation for MEDP, then there is a subset of size OPT over the logarithm of the number of nodes which is routable with congestion 2. Subsequently they showed that it is possible to get within a constant factor of the optimal solution with congestion 4 instead of 2. We strengthen this latter result to show that a constant approximation is possible also with congestion 2 (and this is tight via the integrality gap grid example). We use a basic framework from work by Chekuri et al. At the heart of their approach is a 2-phase algorithm that selects an Okamura-Seymour instance. Each of their phases incurs a factor 2 congestion. It is possible to reduce one of the phases to have congestion 1. In order to achieve an overall congestion 2, however, the two phases must share capacity more carefully. For the Phase 1 problem, we extract a problem called rooted clustering that appears to be an interesting problem class in itself.
机译:我们研究平面图中的最大边不相交路径问题(MEDP)。我们给了一组终端对,希望找到需求的最大可路由子集。即,可以通过边不相交的路径连接的需求子集。众所周知,即使在网格状图上,因此在平面图上,对于这个问题,节点数的平方根的积分间隙也是存在的(Garg等人)。相反,Chekuri等。表明对于平面图,如果LP是MEDP自然线性规划松弛的最佳解决方案,则在节点数的对数上有一个大小为OPT的子集,该子集可以通过拥塞2进行路由。可能会在拥塞4而不是2的情况下获得最优解的常数因子。我们加强了后一个结果,以证明在拥塞2的情况下也可以进行恒定逼近(这在完整性间隙网格示例中很严格)。我们使用来自Chekuri等人的工作的基本框架。他们方法的核心是选择Okamura-Seymour实例的2相算法。它们的每个阶段都会导致2倍的拥塞。可以减少其中一个阶段的拥塞1。但是,为了实现总体拥塞2,这两个阶段必须更仔细地共享容量。对于第1阶段问题,我们提取了一个称为“ rooted clustering”的问题,该问题本身似乎是一个有趣的问题类。

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