Intelligent Search of Correlated Alarms from Database containing Noise Data
Abstract
Alarm correlation plays an important role in improving the service and reliability in modern telecommunications networks. Most previous research of alarm correlation didn't consider the effect of noise data in Database. This paper focuses on the method of discovering alarm correlation rules from database containing noise data. We firstly define two parameters Winfreq and Winadd as the measure of noise data and then present the Robustsearch algorithm to solve the problem. At different size of Winfreq and Winadd, experiments with alarm data containing noise data show that the Robustsearch Algorithm can discover the more rules with the bigger size of Winadd. We also experimentally compare two different interestingness measures of confidence and correlation.
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