Bayesian Fault Detection and Diagnosis in Dynamic Systems
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
A knowledge plane for the internet
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Sophia: an Information Plane for networked systems
ACM SIGCOMM Computer Communication Review
Shrink: a tool for failure diagnosis in IP networks
Proceedings of the 2005 ACM SIGCOMM workshop on Mining network data
PlanetSeer: internet path failure monitoring and characterization in wide-area services
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Scriptroute: a public internet measurement facility
USITS'03 Proceedings of the 4th conference on USENIX Symposium on Internet Technologies and Systems - Volume 4
Learning probabilistic relational models
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Loopy belief propagation as a basis for communication in sensor networks
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
NetProfiler: profiling wide-area networks using peer cooperation
IPTPS'05 Proceedings of the 4th international conference on Peer-to-Peer Systems
Automated compilation of Object-Oriented Probabilistic Relational Models
International Journal of Approximate Reasoning
Trouble shooting interactive web sessions in a home environment
Proceedings of the 2nd ACM SIGCOMM workshop on Home networks
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Internet fault diagnosis today is slow, costly, and error-prone because it requires humans to run diagnostic tests and interpret their results. A fully autonomous self-diagnosing network could greatly improve diagnostic accuracy and efficiency, but such a network requires a common language for expressing diagnostic knowledge and data, and a protocol for distributed probabilistic diagnostic reasoning. In this paper I show how the Common Architecture for Probabilistic Reasoning in the Internet (CAPRI) can satisfy these requirements using probabilistic relational models (PRMs). Preliminary results indicate that CAPRI agents can diagnose HTTP proxy connection failures with over 80% accuracy using TCP failure data collected using an updated version of Planetseer[11].