Smart Storage Data Scrubbing via Attribute Indexing
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Solution Overview
Problem
Existing data scrubbing technologies in storage devices rely on data location information, limiting their ability to intelligently select and correct data based on attributes other than location, which can lead to inefficiencies in error detection and correction.
Innovation Solution
A smart storage device equipped with a storage controller that includes a data analysis engine and an error detection engine, capable of accessing data attribute objects and error correction objects to identify and correct errors based on scrubbing search criteria, utilizing attribute indexes for efficient data selection and reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data scrubbing is performed using only location information, then the scrubbing process is simple to implement, but the ability to intelligently select and correct data based on attributes is limited
Solution Approach 1:
The patent extends the traditional one-dimensional location-based data selection to multi-dimensional attribute-based selection. By introducing data attributes (such as data type, access frequency, criticality) as additional dimensions for identifying target data, the system enables intelligent scrubbing selection beyond mere location information, resolving the contradiction between simplicity and adaptability
Solution Approach 2:
The patent introduces data attributes as an intermediary layer between the scrubbing criterion and the actual data. These attributes act as mediators that enable the storage controller to intelligently select target data without requiring complex direct analysis of all stored data, thus maintaining system simplicity while enhancing selection capability
2Productivity
If all data is scrubbed regardless of attributes, then error detection coverage is maximized, but scrubbing efficiency is reduced
Solution Approach 1:
The patent applies local quality by assigning different scrubbing priorities and attributes to different data elements based on their characteristics. Instead of uniform scrubbing of all data, the system identifies specific data elements with attributes indicating higher error risk or criticality, concentrating scrubbing resources where they are most needed, thus improving efficiency without sacrificing reliability
Solution Approach 2:
The patent implements partial action by performing scrubbing only on selected target data elements that match the scrubbing criterion and have relevant attributes, rather than scrubbing all data. This selective approach improves scrubbing efficiency while the attribute-based selection ensures that critical data elements are not missed, maintaining adequate error detection coverage
Data Source
AI summary
A smart storage device is provided. The smart storage device contains a data analysis engine and an error detection engine. An external controller sends a command indicating that data contained on a storage medium in the smart storage device which meets certain criterion should be scrubbed, and the smart storage device locates that data without the external controller passing the actual location of the data on the storage medium.