Research Article
Detecting Network Events by Analyzing Dynamic Behavior of Distributed Network
@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
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.
