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Storage Device Performance Prediction with CART Models (2004)  (Make Corrections)  (8 citations)
Mengzhi Wang, Kinman Au, Anastassia Ailamaki, Anthony Brockwell, Christos Faloutsos, Gregory R. Ganger



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Abstract: Storage device performance prediction is a key element of self-managed storage systems and application planning tasks, such as data assignment. This work explores the application of a machine learning tool, CART models, to storage device modeling. Our approach predicts a device's performance as a function of input workloads, requiring no knowledge of the device internals. We propose two uses of CART models: one that predicts per-request response times (and then derives aggregate values) and one ... (Update)

Cited by:   More
Continuous resource monitoring for self-predicting DBMS - Dushyanth Narayanan Microsoft (2005)   (Correct)
Informed Data Distribution Selection in a - Self-Predicting Storage System   (Correct)
Modeling the Relative Fitness of Storage Devices - Michael Mesnier Intel   (Correct)

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2.9:   Performance Modeling of Storage Devices Using Machine Learning - Wang (2006)   (Correct)
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0.6:   A Modular, Analytical Throughput Model for Modern Disk Arrays - Uysal, Alvarez, Merchant (2001)   (Correct)

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BibTeX entry:   (Update)

Mengzhi Wang, Kinman Au, Anastassia Ailamaki, Anthony Brockwell, Christos Faloutsos, and Gregory R. Ganger. Storage device performance prediction with CART models. SIGMETRICS Perform. Eval. Rev., 32(1):412--413, 2004. http://citeseer.ist.psu.edu/wang04storage.html   More

@misc{ wang04storage,
  author = "M. Wang and K. Au and A. Ailamaki and A. Brockwell and C. Faloutsos and
    G. Ganger",
  title = "Storage device performance prediction with CART models",
  text = "Mengzhi Wang, Kinman Au, Anastassia Ailamaki, Anthony Brockwell, Christos
    Faloutsos, and Gregory R. Ganger. Storage device performance prediction
    with CART models. SIGMETRICS Perform. Eval. Rev., 32(1):412--413, 2004.",
  year = "2004",
  url = "citeseer.ist.psu.edu/wang04storage.html" }
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