Using pathchar to estimate Internet link characteristics
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Topology Discovery by Active Probing
SAINT-W '02 Proceedings of the 2002 Symposium on Applications and the Internet (SAINT) Workshops
Efficient Probing Techniques for Fault Diagnosis
ICIMP '07 Proceedings of the Second International Conference on Internet Monitoring and Protection
Adaptive diagnosis in distributed systems
IEEE Transactions on Neural Networks
Probabilistic fault diagnosis for IT services in noisy and dynamic environments
IM'09 Proceedings of the 11th IFIP/IEEE international conference on Symposium on Integrated Network Management
Fault diagnosis for high-level applications based on dynamic Bayesian network
APNOMS'09 Proceedings of the 12th Asia-Pacific network operations and management conference on Management enabling the future internet for changing business and new computing services
Efficient active probing for fault diagnosis in large scale and noisy networks
INFOCOM'10 Proceedings of the 29th conference on Information communications
Efficient probe selection for fault localization using the property of submodularity
International Journal of Communication Systems
Adaptive monitoring: a framework to adapt passive monitoring using probing
Proceedings of the 8th International Conference on Network and Service Management
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Past research on probing-based network monitoring provides solutions based on preplanned probing which is computationally expensive, is less accurate, and involves a large management traffic. Unlike preplanned probing, adaptive probing proposes to select probes in an interactive manner sending more probes to diagnose the observed problem areas and less probes in the healthy areas, thereby significantly reducing the number of probes required. Another limitation of most of the work proposed in the past is that it assumes a deterministic dependency information between the probes and the network components. Such an assumption can not be made when complete and accurate network information might not be available. Hence, there is a need to develop network monitoring algorithms that can localize failures in the network even in the presence of uncertainty in the inferred dependencies between probes and network components. In this paper, we propose a fault diagnosis tool with following novel features: (1) We present an adaptive probing based solution for fault diagnosis which is cost-effective, failure resistant, more accurate, and involves less management traffic as compared to the preplanned probing approach. (2) We address the issues that arise with the presence of a non-deterministic environment and present probing algorithms that consider the involved uncertainties in the collected network information.