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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >Algorithms and Stability Analysis for Content Distribution over Multiple Multicast Trees
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Algorithms and Stability Analysis for Content Distribution over Multiple Multicast Trees

机译:多个组播树上内容分发的算法和稳定性分析

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The paper investigates theoretical issues in applying the universal swarming technique to efficient content distribution. In a swarming session, a file is distributed to all the receivers by having all the nodes in the session exchange file chunks. By universal swarming, not only all the nodes in the session, but also some nodes outside the session may participate in the chunk exchange to improve the distribution performance. We present a universal swarming model where the chunks are distributed along different Steiner trees rooted at the source and covering all the receivers. We assume chunks arrive dynamically at the sources and focus on finding stable universal swarming algorithms. To achieve the throughput region, universal swarming usually involves a tree-selection subproblem of finding a min-cost Steiner tree, which is NP-hard. We propose a universal swarming scheme that employs an approximate tree-selection algorithm. We show that it achieves network stability for a reduced throughput region, where the reduction ratio is no more than the approximation ratio of the tree-selection algorithm. We propose a second universal swarming scheme that employs a randomized tree-selection algorithm. It achieves the throughput region, but with a weaker stability result. Comprehensive simulation results support the stability analysis of the algorithms. The proposed schemes and their variants are expected to be useful for infrastructure-based content distribution networks with massive content and relatively stable network environment.
机译:本文研究了将通用群集技术应用于有效内容分发的理论问题。在拥挤的会话中,通过使会话中的所有节点交换文件块,将文件分发给所有接收者。通过通用群集,不仅会话中的所有节点,而且会话外的某些节点也可以参与组块交换,以提高分发性能。我们提出了一个通用的群集模型,其中块沿着源于源头并覆盖所有接收者的不同Steiner树分布。我们假设块动态到达源,并专注于找到稳定的通用群算法。为了获得吞吐量区域,普遍蜂群通常涉及找到最小成本的Steiner树的树选择子问题,该树是NP难的。我们提出了一种采用近似树选择算法的通用群集方案。我们表明,它为减少吞吐量的区域实现了网络稳定性,该区域的减少率不超过树选择算法的近似率。我们提出了第二种通用​​群集方案,该方案采用随机树选择算法。它实现了吞吐量区域,但稳定性较弱。全面的仿真结果支持算法的稳定性分析。预期所提出的方案及其变体将对具有大量内容和相对稳定的网络环境的基于基础设施的内容分发网络有用。

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