Coding-based schemes for fault identification in communication networks
International Journal of Network Management
Real-time protocol analysis for detecting link-state routing protocol attacks
ACM Transactions on Information and System Security (TISSEC)
Statistical Detection of Enterprise NetworkProblems
Journal of Network and Systems Management
A Framework for Event Correlation in Communication Systems
MMNS '01 Proceedings of the 4th IFIP/IEEE International Conference on Management of Multimedia Networks and Services: Management of Multimedia on the Internet
Autonomous recovery in componentized Internet applications
Cluster Computing
Automated Online Monitoring of Distributed Applications through External Monitors
IEEE Transactions on Dependable and Secure Computing
Proceedings of the 44th annual Southeast regional conference
Adaptive active network control and management system (AANCMS)
ICECS'03 Proceedings of the 2nd WSEAS International Conference on Electronics, Control and Signal Processing
Call Forwarding-Based Active Probing for POTS Fault Isolation
Journal of Network and Systems Management
Adaptive active network control and management system (AANCMS)
TELE-INFO'05 Proceedings of the 4th WSEAS International Conference on Telecommunications and Informatics
Chasing a Definition of "Alarm"
Journal of Network and Systems Management
PeerWatch: a fault detection and diagnosis tool for virtualized consolidation systems
Proceedings of the 7th international conference on Autonomic computing
Behavioural Proximity Discovery: an adaptive approach for root cause analysis
International Journal of Business Intelligence and Data Mining
The semantics of alarm definitions: enabling systematic reasoning about alarms
International Journal of Network Management
Research: A LAN fault diagnosis system
Computer Communications
A scheduling-based event correlation scheme for fault identification in communications network
Computer Communications
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In communication networks, a large number of alarms exist to signal any abnormal behavior of the network. As network faults typically result in a number of alarms, correlating these different alarms and identifying their source is a major problem in fault management. The alarm correlation problem is of major practical significance. Alarms that have not been correlated may not only lead to significant misdirected efforts, based on insufficient information, but may cause multiple corrective actions (possibly contradictory) as each alert is handled independently. The paper proposes a general framework to solve the alarm correlation problem. The authors introduce a new model for faults and alarms based on probabilistic finite state machines. They propose two algorithms. The first one acquires the fault models starting from possibly incomplete and incorrect date. The second one correlates alarms in the presence of multiple faults and noisy information. Both algorithms have polynomial time complexity, use an extension of the Viterbi algorithm to deal with the corrupted data, and can be implemented in hardware. As an example, they are applied to analyse faults using data generated by the ANS (Advanced Network and Services, Inc.)/NSF T3 network.