<i>n</i>-Degree and <i>k</i>-Stress Centrality with Parallel Algorithms

Rao Dong-ning; Lin Zhuo-yi; Wei Lai

doi:10.12052/gdutxb.190156

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n-Degree and k-Stress Centrality with Parallel Algorithms

更新时间：2026-05-27

- n-Degree and k-Stress Centrality with Parallel Algorithms
- Vol. 37, Issue 3, Pages: 36-41(2020)
- 作者机构：
  
  1. 广东工业大学计算机学院,广东,广州,510006
  2. 香港大学经济与金融学院,香港,中国,999077
- 作者简介：
- 基金信息：
- DOI：10.12052/gdutxb.190156
  CLC： TP182
- Online First：12 May 2020，
  
  Published：2020
- 稿件说明：
移动端阅览
饶东宁, 林卓毅, 魏来. n-度中心度与k-压力中心度及其并行算法[J]. 广东工业大学学报, 2020, 37(3): 36-41.

Rao Dong-ning, Lin Zhuo-yi, Wei Lai. n-Degree and k-Stress Centrality with Parallel Algorithms[J]. 2020, 37(3): 36-41. DOI: 10.12052/gdutxb.190156.
饶东宁, 林卓毅, 魏来. n-度中心度与k-压力中心度及其并行算法[J]. 广东工业大学学报, 2020, 37(3): 36-41. DOI： 10.12052/gdutxb.190156.

Rao Dong-ning, Lin Zhuo-yi, Wei Lai. n-Degree and k-Stress Centrality with Parallel Algorithms[J]. 2020, 37(3): 36-41. DOI: 10.12052/gdutxb.190156. DOI：

摘要

网络中心度是网络分析的重要指标。文章提出

-度中心度和

-压力中心度以补充网络中心度的研究

此外

并行算法能提高大规模网络的计算效率。为此

在设计网络中心度并行工具包的同时

设计并实现

-度中心度和

-压力中心度的并行算法。工具包的设计基于Spark框架的Pregel方法

并通过BoardEx社交网络测试性能。实验证明工具包的可行性与可拓展性。

Abstract

Network centrality is important for network analysis. Therefore

-Degree and

-Stress centrality are proposed to enrich the analysis options using network centrality. On the other hand

for large scale networks

parallel algorithms are necessary for fast computation. To this end

parallel algorithms for the

-Degree and

-Stress centrality are designed and implemented along with 11 existing centralities in a toolkit. The toolkit is based on Spark Pregel

and tested on the BoardEx social network. Experiments show the feasibility and scalability of the toolkit.

关键词

Keywords

references

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廖志军. 分布式K-Core算法加速求解最大团问题及在金融社交网络中应用[D]. 广州: 暨南大学, 2018.

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n-Degree and k-Stress Centrality with Parallel Algorithms

DOI：10.12052/gdutxb.190156

摘要

Abstract

关键词

Keywords

references