Abstract: With the continuous development of networks, alarm correlation analysis has received extensive attention as an important means of fault diagnosis. However, in a complex network environment, problems such as link interruption, congestion caused by network faults may result in the loss of alarm data, and the amount of transient alarms caused by fault propagation may be massive. These problems make existing rule-based reasoning algorithms are difficult to meet the accuracy and real-time requirements of root cause alarm reasoning. The algorithm based on the characteristics of network alarm uses fuzzy logic-based reasoning strategies and fact-based communication strategies based on probabilistic association models to balance the speed of reasoning while improving the accuracy of reasoning. The algorithm can more effectively correlate alarms. Finally, through simulation experiments, the experimental results show that the Im_Rete algorithm has better performance in terms of speed and accuracy.

Key words: alarm, correlation, rule reasoning, fuzzy logic