Time Series Segmentation for Context Recognition in Mobile Devices
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Clustering intrusion detection alarms to support root cause analysis
ACM Transactions on Information and System Security (TISSEC)
Dynamic syslog mining for network failure monitoring
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
High speed and robust event correlation
IEEE Communications Magazine
Chasing a Definition of "Alarm"
Journal of Network and Systems Management
The semantics of alarm definitions: enabling systematic reasoning about alarms
International Journal of Network Management
Inference of network anomaly propagation using spatio-temporal correlation
Journal of Network and Computer Applications
| Hi-index | 0.00 |
In telecommunication networks, alarms are usually useful for identifying faults, and therefore solving them. However, for large systems the number of alarms produced is so large that the current management systems are overloaded. One way of overcoming this problem is to filter and reduce the number of alarms before the faults can be located. In this paper, we describe a new approach for fault recognition and classification in large telecommunication networks. We introduce a new model and present another way of understanding the alarm correlation problem.