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Distributed k-Core Decomposition

机译：分布式k核分解

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摘要

Several novel metrics have been proposed in recent literature in order to study the relative importance of nodes in complex networks. Among those, k-coreness has found a number of applications in areas as diverse as sociology, proteinomics, graph visualization, and distributed system analysis and design. This paper proposes new distributed algorithms for the computation of the k-coreness of a network, a process also known as k-core decomposition. This technique 1) allows the decomposition, over a set of connected machines, of very large graphs, when size does not allow storing and processing them on a single host, and 2) enables the runtime computation of k-cores in “live” distributed systems. Lower bounds on the algorithms complexity are given, and an exhaustive experimental analysis on real-world data sets is provided.
机译：为了研究复杂网络中节点的相对重要性，最近的文献中提出了几种新颖的度量标准。其中，k-coreness已在社会学，蛋白质组学，图形可视化以及分布式系统分析和设计等领域得到了广泛的应用。本文提出了一种新的分布式算法，用于计算网络的k核，该过程也称为k核分解。此技术1）允许在一组连接的机器上分解非常大的图，但其大小不允许在单个主机上进行存储和处理； 2）允许运行时计算“实时”分布的k核系统。给出了算法复杂度的下限，并提供了对真实数据集的详尽实验分析。

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