Network fault location based on bipartite graphs for communication and information networks

Limin CUI; Qingsu HE; Junsheng WANG; Xin SHI

doi:10.11959/j.issn.1000-0801.2017077

您当前的位置：

首页 >

文章列表页 >

Network fault location based on bipartite graphs for communication and information networks

research and development | 更新时间：2024-06-05

- Network fault location based on bipartite graphs for communication and information networks
- Telecommunications Science Vol. 33, Issue 3, Pages: 76-82(2017)
- 作者机构：
  
  1. 华北电力大学经济与管理学院，北京102206
  2. 国家电网新疆电力公司信息通信公司，新疆乌鲁木齐 830018，北京100084
  3. 国家电网电子商务有限公司，北京 100053
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2017077
  CLC： TP393
- Published Online：2017-03，
  
  Published：20 March 2017
- 稿件说明：
移动端阅览
Limin CUI, Qingsu HE, Junsheng WANG, et al. Network fault location based on bipartite graphs for communication and information networks[J]. Telecommunications science, 2017, 33(3): 76-82.
DOI：

Limin CUI, Qingsu HE, Junsheng WANG, et al. Network fault location based on bipartite graphs for communication and information networks[J]. Telecommunications science, 2017, 33(3): 76-82. DOI： 10.11959/j.issn.1000-0801.2017077.

摘要

国家电网信息通信网络依靠两套运维系统，分别实现对信息网络与通信网络的故障定位与分析，然而通信网络故障往往会引发信息网络故障，如何高效精确地进行通信信息网络故障联合定位是亟需解决的问题。针对信息通信网络的联合故障定位问题，提出了基于二分图模型的故障联合定位算法。首先依据通信网网络节点的关联性对网络分簇，并将每一簇作为一个子域。其次在每个子域内建立基于二分图的故障关联影响模型，最终利用目标排序法并行地对多个子域内网络故障进行分析，从而实现通信信息网络关联故障高效精确的联合定位。实验结果表明，该联合故障定位分析方法的故障诊断率达85%～95%。

Abstract

The current State Grid communication and information networks rely on two separate network management systems.Such management structure brings challenges to network fault location

which calls for joint network fault analyze method. Grasping the transmission correlation of network nodes

a joint network fault location mechanism based on bipartite graph model was proposed.Firstly

network nodes were clustered into multiple sub-domains based on their fault correlation.Then

the bipartite graph fault correlation model was established for each sub-domain.Finally

the target sorting method was applied to locate network faults in every sub-domain simultaneously.Simulation experiments show that this method can locate network faults with high accuracy.

关键词

Keywords

references

杜晓丽，朱程荣，熊齐邦 . 一种基于依赖图的故障定位算法 [J ] . 计算机应用， 2004 , 24 : 67 - 69 .

DU X L , ZHU C R , XIONG Q B . A fault location algorithm based on dependency graph [J ] . Journal of Computer Applications , 2004 , 24 : 67 - 69 .

HE M , ZHANG J . A dependency graph approach for fault detection and localization towards secure smart grid [J ] . IEEE Transactions on Smart Grid , 2011 , 2 ( 2 ): 342 - 351 .

邓歆，孟洛明 . 基于贝叶斯网络的通信网告警相关性和故障诊断模型 [J ] . 电子与信息学报， 2007 , 5 : 1182 - 1186 .

DENG X , MENG L M . Bayesian networks based alarm correlation and fault diagnosis in communication networks [J ] . Journal of electronics ＆ Information Technology , 2007 ( 5 ): 1182 - 1186 .

王开选，杨峥，邱雪松，等 . 面向影响分析的电力通信网故障定位算法 [J ] . 北京邮电大学学报， 2014 ( 4 ).

WANG K X , YANG Z , QIU X S , et al . Algorithm of fault locating on impact analysis in power communications network [J ] . Journal of Beijing University of Posts and Telecommunications , 2014 ( 4 ).

曾飞，张勇，刘玙，等 . 电力系统故障诊断的时序模糊逻辑推理方法 [J ] . 华北电力大学学报 ( 自然科学版 )， 2014 , 41 ( 1 ): 7 - 14 .

ZENG F , ZHANG Y , LIU Y , et al . A temporal and fuzzy logic inference based method for power system fault diagnosis [J ] . Journal of North China Electric Power University ( Natural Science Edition )， 2014 , 41 ( 1 ): 7 - 14 .

YU L , SUN Y , LI K J , et al . An improved genetic algorithm based on fuzzy inference theory and its application in distribution network fault location [C ] // 2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA) , June 5 - 7 , 2016 , Hefei, China . New Jersey : IEEE Press , 2016 : 1411 - 1415 .

戚勇，李千目，刘凤玉 . 基于BP神经网络的网络智能诊断系统 [J ] . 微电子学与计算机， 2004 , 21 ( 10 ): 10 - 13 .

QI Y , LI Q M , LIU F Y . Network fault intelligent diagnosis base on BP neural network [J ] . Microelectronics＆Computer , 2004 , 21 ( 10 ): 10 - 13 .

张禹 . 模糊神经网络在移动通信网故障诊断中的应用 [D ] ．天津：天津理工大学， 2010 : 22 - 32 .

ZHANG Y . The application of fuzzy neural network in mobile communication network fault diagnosis [D ] . Tianjin:Tianjin University of Technology , 2010 : 22 - 32 .

赵灿明，李祝红，陶磊，等 . 基于故障传播模型与监督学习的电力通信网络故障定位 [J ] . 计算机应用， 2016 ( 4 ): 905 - 908 .

ZHAO C M , LI Z H , TAO L , et al . Fault localization for electric power communication network based on fault propagation model and supervised learning [J ] . Journal of Computer Applications , 2016 ( 4 ): 905 - 908 .

杨娇 . 二分图网络故障传播模型与故障诊断算法研究 [D ] ．沈阳：东北大学， 2011 .

YANG J . Bipartion Graph Fault Propagation Model and Diagnosis Algorithm [D ] . Shenyang: Northeastern University , 2011 .

张敏，姚良威，侯宇 . 基于向量和矩阵的频繁项集挖掘算法研究 [J ] . 计算机工程与设计， 2013 , 34 ( 3 ): 939 - 943 .

ZHANG M , YAO L W , HOU Y . Research of frequent itemsets mining algorithm based on vector and matrix [J ] . Computer Engineering and Design , 2013 , 34 ( 3 ): 939 - 943 .

温大伟，谢文环 . 求解整数规划的一种隐枚举法 [J ] . 数学教学研究， 2012 , 31 ( 11 ): 60 - 61 .

WEN D W , XIE W H . An implicit enumeration method for solving integer programming [J ] . Journal of Mathematical Study , 2012 , 31 ( 11 ): 60 - 61 .

Views

944

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

No data

Related Author

No data

Related Institution

No data

⁰