Distributed Monitoring of Concurrent and Asynchronous Systems*
Discrete Event Dynamic Systems
Situation recognition: representation and algorithms
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Towards an autonomic network architecture for self-healing in telecommunications networks
AIMS'10 Proceedings of the Mechanisms for autonomous management of networks and services, and 4th international conference on Autonomous infrastructure, management and security
Journal of Mobile Multimedia
Practical experiences with chronics discovery in large telecommunications systems
SLAML '11 Managing Large-scale Systems via the Analysis of System Logs and the Application of Machine Learning Techniques
Definition and performance evaluation of a fault localization technique for an NGN IMS network
IEEE Transactions on Network and Service Management
| Hi-index | 0.00 |
This paper proposes an approach to automatise the management of faults, covering the different segments of a network, and the end-to-end services deployed over them. This is model-based approach addressing the two weaknesses of model-based diagnosis namely deriving an accurate model and dealing with huge models. To address the first point, we propose a solution called self-modeling that formulates off-line generic patterns of the model, and identifies on-line the instances of these patterns that are deployed in the managed network. The second point is addressed by an active (self-)diagnosis engine, based on a Bayesian network formalism. This consists in reasoning on a progressively growing fragment of the network model: more observations are collected and new tests are performed until the faults are localized with sufficient confidence. This active diagnosis approach is experimented to perform cross-layer and cross-segment alarm management on an IMS network.