Computer Science ›› 2018, Vol. 45 ›› Issue (11A): 535-538.

• Interdiscipline & Application • Previous Articles     Next Articles

Application of Sequence Pattern Mining in Communication Network Alarm Prediction

ZHANG Guang-lan, YANG Qiu-hui, CHENG Xue-mei, JIANG Ke, WANG Shuai, TAN Wu-kun   

  1. School of Software,Sichuan University,Chengdu 610000,China
  • Online:2019-02-26 Published:2019-02-26

Abstract: Alarm prediction is one of the techniques that ensures the stability and reliability of the entire network.Exis-ting alarm forecasting technologies have defects such as not considering the time sequence of warning data and difficult to obtain the priori knowledge.Therefore,this paper proposed a sequence pattern mining method based on topological constraints to find a meaningful alarm sequence pattern.This algorithm mainly considers the topological connections between network nodes and takes them as constraints for mining the alarm sequence pattern.In order to find non-frequent major alarm mode,it improves pruning of sequential pattern mining,preserves sequence patterns containing major alarms directly.Experiments show that the alarm sequence mode mined by the sequential pattern mining method based on topological constraints can improve the accuracy and efficiency of the network alarm prediction and predict the infrequent “major” alarms more accurately.

Key words: Alarm prediction, Communication network, Network topology architecture, Sequence pattern mining

CLC Number: 

  • TP311
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