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New Benchmarks for Large-Scale Networks with Given Maximum Degree and Diameter

机译:给定最大度数和最大直径的大型网络新基准

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Large-scale networks have become ubiquitous elements of our society. Modern social networks, supported by communication and travel technology, have grown in size and complexity to unprecedented scales. Computer networks, such as the Internet, have a fundamental impact on commerce, politics and culture. The study of networks is also central in biology, chemistry and other natural sciences. Unifying aspects of these networks are a small maximum degree and a small diameter, which are also shared by many network models, such as small-world networks. Graph theoretical methodologies can be instrumental in the challenging task of predicting, constructing and studying the properties of large-scale networks. This task is now necessitated by the vulnerability of large networks to phenomena such as cross-continental spread of disease and botnets (networks of malware). In this article, we produce the new largest known networks of maximum degree 17 ≤ Δ ≤ 20 and diameter 2 ≤ D ≤ 10, using a wide range of techniques and concepts, such as graph compounding, vertex duplication, Kronecker product, polarity graphs and voltage graphs. In this way, we provide new benchmarks for networks with given maximum degree and diameter, and a complete overview of state-of-the-art methodology that can be used to construct such networks.
机译:大型网络已成为我们社会无处不在的元素。在通讯和旅行技术的支持下,现代社交网络的规模和复杂性已达到前所未有的规模。诸如Internet之类的计算机网络对商业,政治和文化具有根本的影响。网络的研究在生物学,化学和其他自然科学中也很重要。这些网络的统一方面是最大程度较小且直径较小,许多网络模型(例如小世界网络)也共享这些特征。图论方法论可以在预测,构建和研究大型网络的特性这一艰巨的任务中发挥作用。大型网络容易受到诸如疾病和僵尸网络(恶意软件网络)的跨洲传播之类的现象的影响,现在需要执行此任务。在本文中,我们使用广泛的技术和概念(例如图形合成,顶点复制,Kronecker乘积,极性图和等),产生了最大度数最大为17≤Δ≤20和直径为2≤D≤10的新的最大网络。电压图。通过这种方式,我们为具有最大程度和最大直径的网络提供了新的基准,并提供了可用于构建此类网络的最新方法的完整概述。

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