In the area of network performance and discovery, network tomography focuses on reconstructing network properties using only end-to-end measurements at the application layer. One challenging problem in network tomography is reconstructing available bandwidth along all links during multiple source/multiple destination transmissions. The traditional measurement procedures used for bandwidth tomography are extremely time consuming. We propose a novel solution to this problem. Our method counts the fragments exchanged during a BitTorrent broadcast. While this measurement has a high level of randomness, it can be obtained very efficiently, and aggregated into a reliable metric. This data is then analyzed with state-of-the-art algorithms, which correctly reconstruct logical clusters of nodes interconnected by high bandwidth, as well as bottlenecks between these logical clusters. Our experiments demonstrate that the proposed two-phase approach efficiently solves the presented problem for a number of settings on a complex grid infrastructure.

中文翻译：

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使用Bittorrent广播和聚类算法的异构网络中高效可靠的网络层析成像

在网络性能和发现领域，网络断层扫描专注于仅使用应用程序层的端到端测量来重建网络属性。网络断层扫描中的一个具有挑战性的问题是在多个源/多个目标传输期间沿所有链路重构可用带宽。用于带宽层析成像的传统测量程序非常耗时。我们为这个问题提出了一种新颖的解决方案。我们的方法计算在BitTorrent广播期间交换的片段。尽管此度量具有高度的随机性，但可以非常有效地获得它，并将其汇总为可靠的度量。然后，使用最新算法对这些数据进行分析，该算法可以正确地重建通过高带宽互连的节点的逻辑集群，以及这些逻辑集群之间的瓶颈。我们的实验表明，所提出的两阶段方法可以有效解决复杂网格基础结构上许多设置的问题。