Frontiers of Data and Computing ›› 2021, Vol. 3 ›› Issue (6): 142-150.

doi: 10.11871/jfdc.10-1649.2021.06.011

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Subtle Aberration Monitoring of Link Traffic Based on Outlier Detection

LI Jingjing1,2,*(),YANG Xiaolin1,2(),LI Jun1,2(),HE Qunhui1()   

  1. 1. Computer Network Information Center, Chinese Academy of Sciences, Beijing 100083, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2021-05-11 Online:2021-12-20 Published:2022-01-26
  • Contact: LI Jingjing;;;


[Objective] The subtle aberration of network traffic has a harmful influence on scientific research precision joint observation. The fixed threshold network traffic monitoring currently used can only effectively warn the link resource consumption, but cannot monitor the subtle aberration of branch line traffic.[Methods] Therefore, we propose a new link traffic warning model which can monitor subtle aberration and trigger alarm based on the improved outlier detection method in this study to support the network management of CSTNet. The model can implement fast monitoring and early warning of subtle aberration of the link traffic by fast calculation of deviation between the observed traffic value and dynamic baseline in sliding time window. [Conclusions] Experiments in the real operation of CSTNet demonstrate that the warning trigger points are all consistent with the abnormal record points in the network operation and diagnostic record, which has the feasibility of engineering application.

Key words: outlier detection, link traffic, monitoring model, dynamic baseline