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Unifying Unknown Nodes in the Internet Graph Using Semisupervised Spectral Clustering

机译:使用半监督谱聚类统一Internet图中的未知节点

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Most research on Internet topology is based on active measurement methods. A major difficulty in using these tools is that one comes across many unresponsive routers. Different methods of dealing with these anonymous nodes to preserve the connectivity of the real graph have been suggested. One of the more practical approaches involves using a placeholder for each unknown, resulting in multiple copies of every such node. This significantly distorts and inflates the inferred topology. Our goal in this work is to unify groups of placeholders in the IP-level graph. We introduce a novel clustering algorithm based on semisupervised spectral embedding of all the nodes followed by clustering of the anonymous nodes in the projected space. Experimental results on real internet data are provided, that show good similarity to the true networks.
机译:Internet拓扑的大多数研究都是基于主动测量方法。使用这些工具的主要困难在于,它会遇到许多无响应的路由器。已经提出了处理这些匿名节点以保持真实图的连通性的不同方法。一种更实用的方法涉及为每个未知数使用占位符,从而导致每个此类节点具有多个副本。这会极大地扭曲和扩大推断的拓扑。我们这项工作的目标是统一IP级别图中的占位符组。我们介绍了一种基于所有节点的半监督频谱嵌入,然后在投影空间中对匿名节点进行聚类的新颖聚类算法。提供了有关真实互联网数据的实验结果,这些结果显示出与真实网络的良好相似性。

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