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Data storage system with trained predictive cache management engine

  • US 6,163,773 A
  • Filed: 05/05/1998
  • Issued: 12/19/2000
  • Est. Priority Date: 05/05/1998
  • Status: Expired due to Fees
First Claim
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1. A method of training a neural network to evaluate cached datasets, where dataset accesses are logged as dataset entries of a dataset access log, the method comprising:

  • designating multiple predetermined event triggers, each trigger comprising a predetermined event occurring in association with any one of the datasets contained in the cache;

    in response to the occurrence of an event trigger, the event trigger occurring at a trigger time and in association with a first dataset represented in the dataset access log,consulting the dataset access log to identify a latest access time of the first dataset;

    establishing one or more training times in an interval from the trigger time to the latest access time;

    for each training time, storing selected training input including characteristics of the first dataset in a training record, the characteristics having been exhibited by the first dataset at the training time and also storing training output including a representation of value provided by having the first dataset present in the cache to satisfy future requests for access to the first dataset; and

    according to a predetermined schedule, providing the training input from the training record as input to a single output back propagation neural network yielding a neural network output, and training the neural network according to any difference between the training output and the neural network output.

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