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大规模网络中k点连通分量的分布式计算

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近年来,k点连通分量(k-VCC)由于其结构内聚性而成为图分析中的一个关键点.k-VCC是指在删除k-1个顶点后剩余的图仍然连通的子图.现有算法对k-VCC问题的研究主要集中在单机环境下,为此,本文设计了一个分布式计算框架,挖掘给定图中的所有k-VCC,将挖掘大图的问题划分为多个更小的子图以并发执行挖掘任务.通过实验证明了所提出的分布式方法的有效性和高效性.
Distributed Computation of k-Vertex Connectivity Components in Large-scale Networks
In recent years,the k-vertex connected component(k-VCC)has become a key point in graph analysis due to its structural cohesion.k-VCCs are subgraphs whose remaining graphs are still connected after removing k-1 vertices.Existing algorithms for the k-VCC problem mainly focus on a single-computer environment.For this reason,in this paper,we design a distributed computational framework to mine all the k-VCCs in a given graph,and divide the problem of mining a large graph into multiple smaller subgraphs to perform the mining task concurrently.The effectiveness and efficiency of the proposed distributed approach is demonstrated experimentally.

k-vertex connected componentsdistributed computinggraph partitioning

王立松

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北方工业大学信息学院,北京 100144

k点连通分量 分布式计算 图划分

2024

软件
中国电子学会 天津电子学会

软件

影响因子:1.51
ISSN:1003-6970
年,卷(期):2024.45(7)