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首页> 外文期刊>Theoretical computer science >Sparse certificates for 2-connectivity in directed graphs
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Sparse certificates for 2-connectivity in directed graphs

机译:定向图中的2连接性稀疏证书

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Motivated by the emergence of large-scale networks in today's applications, we show how to compute efficiently smaller subgraphs that maintain some properties of an input graph. In particular, let G be a strongly connected directed graph. We consider the problem of computing the smallest strongly connected spanning subgraph of G that maintains certain connectivity relations of G. Specifically, for 2-edge-connectivity, we consider how to maintain the maximal 2-edge-connected subgraphs (2ECS) or the 2-edge-connected components (2ECC) of G, or both the maximal 2-edge-connected subgraphs and the 2-edge-connected components (2EC). Similarly, for 2-vertex-connectivity, we consider how to maintain the maximal 2-vertex-connected subgraphs (2VCS) or the 2-vertex-connected components (2VCC) of G, or both the maximal 2-vertex-connected subgraphs and the 2-vertex-connected components (2VC). All those problems are NP-hard, and thus we are interested in approximation algorithms. Additionally, we aim at designing algorithms with a good practical performance, so that they are able to scale effectively to very large graphs. While for 2ECS and 2VCS one can obtain an approximation ratio smaller than 2 by combining previously known results, providing good approximations for the 2-edge and the 2-vertex-components case seems more challenging. Here, we present linear-time approximation algorithms that achieve the following approximation guarantees:
机译:通过在当今的应用中出现大型网络的出现,我们展示了如何计算维护输入图的一些属性的有效较小的子图。特别是,设g是一个强连接的指示图。我们考虑计算G的最小强烈连接跨越的问题,该跨越G的跨越G.具体地,对于2边缘连接,我们考虑如何维护最大的2边缘连接的子图(2EC)或2 -Edge连接的组件(2ECC)G,或最大的2边缘连接的子图和双边缘连接的组件(2EC)。类似地,对于2 - 顶点连接,我们考虑如何维护G的最大2顶点连接的子图(2VC)或G的2个顶点连接的组件(2VCC),或最大2-顶点连接的子图和2顶点连接的组件(2VC)。所有这些问题都是NP - 硬,因此我们对近似算法感兴趣。此外,我们的目标是使用良好的实际表现设计算法,因此它们能够有效地扩展到非常大的图形。虽然对于2ECS和2VCS,通过组合先前已知的结果,可以获得小于2的近似比,从而为2边缘提供良好的近似,并且2-顶点 - 分量案例似乎更具挑战性。在这里,我们呈现线性时间近似算法,该近似算法实现了以下近似保证:

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