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A Superstabilizing log(n)-Approximation Algorithm for Dynamic Steiner Trees

机译:一种巨大的Log(n) - 动态施蒂纳树的批量估计算法

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This paper proposes a fully dynamic self-stabilizing algorithm for the Steiner tree problem. The Steiner tree problem aims at constructing a Minimum Spanning Tree (MST) over a subset of nodes called Steiner members, or Steiner group usually denoted S. Steiner trees are good candidates to efficiently implement communication primitives such as publish/subscribe or multicast, essential building blocks in the design of middleware architectures for the new emergent networks (e.g. P2P, sensor or adhoc networks). Our algorithm returns a log |S|-approximation of the optimal Steiner tree. It improves over existing solutions in several ways. First, it is fully dynamic, in other words it withstands the dynamism when both the group members and ordinary nodes can join or leave the network. Next, our algorithm is self-stabilizing, that is, it copes with nodes memory corruption. Last but not least, our algorithm is superstabilizing. That is, while converging to a correct configuration (i.e., a Steiner tree) after a modification of the network, it keeps offering the Steiner tree service during the stabilization time to all members that have not been affected by this modification.
机译:本文提出了一种完全动态的施泰格树问题的自我稳定算法。 Steiner树问题旨在构建一个名为Steiner成员的节点子集的最小生成树(MST),或者施泰纳群通常表示S. Steiner树是良好的候选者,以有效地实施通信基元,例如发布/订阅或多播,基本建筑物等通信基元用于新的紧急网络的中间件架构设计的块(例如P2P,传感器或ADHOC网络)。我们的算法返回最佳Steiner树的logximation。它以多种方式提高了现有解决方案。首先,它是完全动态的,换句话说,当组成员和普通节点都可以加入或离开网络时,它符合其抵消动力。接下来,我们的算法是自稳定的,即它与节点内存损坏。最后但并非最不重要的是,我们的算法是夸大的。也就是说,在网络修改之后将其融合到正确的配置(即,施蒂纳树)的同时,它在稳定时间期间保留稳定性树服务,以便在不受该修改的影响。

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