Analyzing Disturbed Diffusion on Networks

机译：分析网络上的干扰扩散

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This work provides the first detailed investigation of the disturbed diffusion scheme FOS/C introduced in as a type of diffusion distance measure within a graph partitioning framework related to Lloyd's k-means algorithm. After outlining connections to distance measures proposed in machine learning, we show that FOS/C can be related to random walks despite its disturbance. Its convergence properties regarding load distribution and edge flow characterization are examined on two different graph classes, namely torus graphs and distance-transitive graphs (including hypercubes), representatives of which are frequently used as interconnection networks.

机译：这项工作提供了对扰动扩散方案FOS / C的首次详细研究，该扰动扩散方案是在与Lloyd's k-means算法相关的图分区框架内作为一种扩散距离度量引入的。在概述了与机器学习中提出的距离度量的联系之后，我们表明FOS / C可以与随机行走相关联，尽管它会受到干扰。在两个不同的图类（即环面图和距离传递图（包括超立方体））上检查了其关于负载分布和边缘流特征的收敛特性，它们的代表经常用作互连网络。

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来源
《Algorithms and Computation; Lecture Notes in Computer Science; 4288》|2006年|429-438|共10页
会议地点 Kolkata(IN)
作者
Henning Meyerhenke; Thomas Sauerwald;
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作者单位

Universitaet Paderborn Fakultaet fuer Elektrotechnik, Informatik und Mathematik Fuerstenallee 11, D-33102 Paderborn, Germany;

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会议组织
原文格式 PDF
正文语种 eng
中图分类理论、方法;
关键词
disturbed diffusion; diffusion distance; random walks;

机译：干扰扩散；扩散距离随机漫步;

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机译：分析网络上的干扰扩散

Analyzing Disturbed Diffusion on Networks

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