Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Schemes for fault identification in communication networks
IEEE/ACM Transactions on Networking (TON)
Centralized vs. distributed fault localization
Proceedings of the fourth international symposium on Integrated network management IV
A random graph model for massive graphs
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
On the origin of power laws in Internet topologies
ACM SIGCOMM Computer Communication Review
BRITE: Universal Topology Generation from a User''s Perspective
BRITE: Universal Topology Generation from a User''s Perspective
Probabilistic fault diagnosis in communication systems through incremental hypothesis updating
Computer Networks: The International Journal of Computer and Telecommunications Networking
Probabilistic fault localization in communication systems using belief networks
IEEE/ACM Transactions on Networking (TON)
Multidomain Diagnosis of End-to-End Service Failures in Hierarchically Routed Networks
IEEE Transactions on Parallel and Distributed Systems
Factor graphs and the sum-product algorithm
IEEE Transactions on Information Theory
High speed and robust event correlation
IEEE Communications Magazine
IEEE Communications Magazine
An infrastructure for the management of dynamic service networks
IEEE Communications Magazine
Multidomain Diagnosis of End-to-End Service Failures in Hierarchically Routed Networks
IEEE Transactions on Parallel and Distributed Systems
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
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Probabilistic inference was shown effective in the nondeterministic diagnosis of end-to-end service failures when applied in a centralized management system where the manager possesses a global knowledge of the system structure and state. Since many networks are organized into multiple administrative domains that may be unable to share configuration and state information, these centralized techniques are not applicable to them. This paper proposes a fault localization technique suitable for multidomain networks with hierarchical routing. The proposed technique divides the computational effort and system knowledge among multiple, hierarchically organized managers. Each manager performs fault localization in the domain it manages and requires only the knowledge of its own domain. We show through simulation that the proposed approach not only improves the feasibility of fault localization in multidomain networks, but also increases the effectiveness of probabilistic diagnosis and makes it realizable in networks of considerable size.