Stardust: tracking activity in a distributed storage system
SIGMETRICS '06/Performance '06 Proceedings of the joint international conference on Measurement and modeling of computer systems
Towards an autonomic computing testbed
HotAC II Hot Topics in Autonomic Computing on Hot Topics in Autonomic Computing
Observer: keeping system models from becoming obsolete
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Efficient reduction of access latency through object correlations in virtual environments
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FAST'08 Proceedings of the 6th USENIX Conference on File and Storage Technologies
A versatile policy toolkit supporting run-time policy reconfiguration
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Support for automatic diagnosis and dynamic configuration of scalable storage systems
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HiPC'08 Proceedings of the 15th international conference on High performance computing
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ISTASC'10 Proceedings of the 10th WSEAS international conference on Systems theory and scientific computation
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Proceedings of the 2nd ACM Symposium on Cloud Computing
Predico: a system for what-if analysis in complex data center applications
Middleware'11 Proceedings of the 12th ACM/IFIP/USENIX international conference on Middleware
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Predico: a system for what-if analysis in complex data center applications
Proceedings of the 12th International Middleware Conference
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Analytical modeling for what-if analysis in complex cloud computing applications
ACM SIGMETRICS Performance Evaluation Review
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PDSW '13 Proceedings of the 8th Parallel Data Storage Workshop
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Systems should be self-predicting. They should continuously monitor themselves and provide quantitative answers to What...if questions about hypothetical workload or resource changes. Self-prediction would significantly simplify administrators' decision making, such as acquisition planning and performance tuning, by reducing the detailed workload and internal system knowledge required. This paper describes and evaluates support for self-prediction in a cluster-based storage system and its application to What...if questions about data distribution selection.