Detection of abrupt changes: theory and application
Detection of abrupt changes: theory and application
Measuring Web performance in the wide area
ACM SIGMETRICS Performance Evaluation Review
Future Generation Computer Systems - Special issue on metacomputing
A non-instrusive, wavelet-based approach to detecting network performance problems
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Optimal Histograms with Quality Guarantees
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Distributed DNS troubleshooting
Proceedings of the ACM SIGCOMM workshop on Network troubleshooting: research, theory and operations practice meet malfunctioning reality
Failure Diagnosis Using Decision Trees
ICAC '04 Proceedings of the First International Conference on Autonomic Computing
ICAC '05 Proceedings of the Second International Conference on Automatic Computing
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
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Webprofiler: cooperative diagnosis of web failures
COMSNETS'10 Proceedings of the 2nd international conference on COMmunication systems and NETworks
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Content providers base their business on their ability to receive and answer requests from clients distributed across the Internet. Since disruptions in the flow of these requests directly translate into lost revenue, there is tremendous incentive to diagnose why some requests fail and prod the responsible parties into corrective action. However, a content provider has only limited visibility into the state of the Internet outside its domain. Instead, it must mine failure diagnoses from available information sources to infer what is going wrong and who is responsible.Our ultimate goal is to help Internet content providers resolve reliability problems in the wide-area network that are affecting end-user perceived reliability. We describe two algorithms that represent our first steps towards enabling content providers to extract actionable debugging information from content provider logs, and we present the results of applying the algorithms to a week's worth of logs from a large content provider, during which time it handled over 1 billion requests originating from over 10 thousand ASes.