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Graphon-Based Visual Abstraction for Large Multi-Layer Networks

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PRE
AI
Z
Ziliang Wu
朱
朱闽峰 (Minfeng Zhu)
Z
Zhaosong Huang
J
Junxu Chen
T
Tiansheng Zhang
S
Shengbing Shi
H
Hao Li
柏
柏强 (Qiang Bai)
H
Hongchao Qu
X
Xiuqi Huang
陈
陈为 (Wei Chen)
DOI：10.1109/TVCG.2025.3581034delete
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摘要

摘要

En 中文
图可视化技术为提供云计算系统的全面概览和洞察提供了基础框架，有助于实现高效管理并确保其可用性和可靠性。尽管更大规模的云计算架构在计算和存储能力上有所增强，但由于层次异质性、可扩展性和数据不完整性等问题，它们给传统的基于图的可视化带来了显著挑战。本文提出了一种新颖的抽象方法来可视化大型多层网络。我们的方法利用图灵（graphons），即网络层的概率表示，包含三个核心步骤：层内汇总以识别稳定和易变的子结构、层间混合以对齐异构网络层，以及一种情境感知的多层联合采样技术，旨在缩小网络规模同时保留关键拓扑特征。通过将复杂的网络数据抽象为可管理的加权图，每个图描绘一个独特的网络层，我们的方法使这些复杂系统在标准计算硬件上变得可访问。我们通过案例研究、定量实验和专家评估验证了我们的方法论，展示了其在管理大型多层网络中的有效性，以及其在更广泛的网络类型（如交通网络和社会网络）中的适用性。
Keyword:
Multi-layer networks
network abstraction
network visualization

期刊

IEEE Transactions on Visualization and Computer Graphics 封面图
IEEE Transactions on Visualization and Computer Graphics
IF:
6.5
论文数:
337
被引数:
2.2W

机构

H
huawei cloud computing technologies company
学者数:
4
论文数: 1
被引数: 0
Z
zhejiang university
学者数:
17.7W
论文数: 12.1W
被引数: 152
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