Data restore process using a probability distribution model for efficient caching of data
Abstract:
Described is a system (and method) that may implement a more intelligent mechanism for managing caching data as part of a data restore process. The system may utilize a read-ahead cache that leverages a statistical probability. More specifically, the system may model a data restore pattern using a binomial probability distribution to dynamically enable when data is stored to read-ahead cache. Accordingly, the system may enable/disable a read-ahead cache setting at any point during the restore process by dynamically adjusting a sequential read threshold according to a determined statistical probability. For example, the system may determine such a dynamical setting based on a Binomial Probability Density Function (PDF) and/or a Cumulative Distribution Function (CDF) to calculate real-time thresholds.
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