99 research outputs found

    Minimum Cuts in Geometric Intersection Graphs

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    Let D\mathcal{D} be a set of nn disks in the plane. The disk graph GDG_\mathcal{D} for D\mathcal{D} is the undirected graph with vertex set D\mathcal{D} in which two disks are joined by an edge if and only if they intersect. The directed transmission graph GDG^{\rightarrow}_\mathcal{D} for D\mathcal{D} is the directed graph with vertex set D\mathcal{D} in which there is an edge from a disk D1DD_1 \in \mathcal{D} to a disk D2DD_2 \in \mathcal{D} if and only if D1D_1 contains the center of D2D_2. Given D\mathcal{D} and two non-intersecting disks s,tDs, t \in \mathcal{D}, we show that a minimum ss-tt vertex cut in GDG_\mathcal{D} or in GDG^{\rightarrow}_\mathcal{D} can be found in O(n3/2polylogn)O(n^{3/2}\text{polylog} n) expected time. To obtain our result, we combine an algorithm for the maximum flow problem in general graphs with dynamic geometric data structures to manipulate the disks. As an application, we consider the barrier resilience problem in a rectangular domain. In this problem, we have a vertical strip SS bounded by two vertical lines, LL_\ell and LrL_r, and a collection D\mathcal{D} of disks. Let aa be a point in SS above all disks of D\mathcal{D}, and let bb a point in SS below all disks of D\mathcal{D}. The task is to find a curve from aa to bb that lies in SS and that intersects as few disks of D\mathcal{D} as possible. Using our improved algorithm for minimum cuts in disk graphs, we can solve the barrier resilience problem in O(n3/2polylogn)O(n^{3/2}\text{polylog} n) expected time.Comment: 11 pages, 4 figure

    Polynomial time algorithms for multicast network code construction

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    The famous max-flow min-cut theorem states that a source node s can send information through a network (V, E) to a sink node t at a rate determined by the min-cut separating s and t. Recently, it has been shown that this rate can also be achieved for multicasting to several sinks provided that the intermediate nodes are allowed to re-encode the information they receive. We demonstrate examples of networks where the achievable rates obtained by coding at intermediate nodes are arbitrarily larger than if coding is not allowed. We give deterministic polynomial time algorithms and even faster randomized algorithms for designing linear codes for directed acyclic graphs with edges of unit capacity. We extend these algorithms to integer capacities and to codes that are tolerant to edge failures
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