Communications and Networking. 13th EAI International Conference, ChinaCom 2018, Chengdu, China, October 23-25, 2018, Proceedings

Research Article

Detecting Network Events by Analyzing Dynamic Behavior of Distributed Network

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  • @INPROCEEDINGS{10.1007/978-3-030-06161-6_63,
        author={Haishou Ma and Yi Xie and Zhen Wang},
        title={Detecting Network Events by Analyzing Dynamic Behavior of Distributed Network},
        proceedings={Communications and Networking. 13th EAI International Conference, ChinaCom 2018, Chengdu, China, October 23-25, 2018, Proceedings},
        proceedings_a={CHINACOM},
        year={2019},
        month={1},
        keywords={Behavior analysis Event detection Network modeling},
        doi={10.1007/978-3-030-06161-6_63}
    }
    
  • Haishou Ma
    Yi Xie
    Zhen Wang
    Year: 2019
    Detecting Network Events by Analyzing Dynamic Behavior of Distributed Network
    CHINACOM
    Springer
    DOI: 10.1007/978-3-030-06161-6_63
Haishou Ma1, Yi Xie1,*, Zhen Wang1
  • 1: Sun Yat-sen University
*Contact email: xieyi5@mail.sysu.edu.cn

Abstract

Detecting network events has become a prevalent task in various network scenarios, which is essential for network management. Although a number of studies have been conducted to solve this problem, few of them concern about the universality issue. This paper proposes a General Network Behavior Analysis Approach (GNB2A) to address this issue. First, a modeling approach is proposed based on hidden Markov random field. Markovianity is introduced to model the spatio-temporal context of distributed network and stochastic interaction among interconnected and time-continuous events. Second, an expectation maximum algorithm is derived to estimate parameters of the model, and a maximum a posteriori criterion is utilized to detect network events. Finally, GNB2A is applied to three network scenarios. Experiments demonstrate the generality and practicability of GNB2A.