Data Storage Error Tolerance Selection Method
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Solution Overview
Problem
Data storage devices face reduced storage capacity and increased risk of reading and writing failures due to undetected bad data columns consuming the error correction ability of error correction codes, necessitating a method to balance error tolerance between bad data columns and error correction ability.
Innovation Solution
An error tolerance selecting method for data storage devices that writes, reads, and compares data blocks to calculate error bits, identifies bad data columns, and adjusts error tolerance lists to maximize error correction ability by determining the number of bad data columns within the device's error correction limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the number of bad data columns is increased to improve storage capacity, then more data can be stored, but the error correction ability of the error correction code is reduced
Solution Approach 1:
The patent applies preliminary action by detecting and marking bad data columns before they consume error correction resources. The method performs write operations to test data columns, reads back the written data, compares it with the original write data to identify error bits, and marks columns with excessive error bits as bad data columns in advance. This prevents bad data columns from consuming error correction ability during normal operation, thereby resolving the contradiction between storage capacity and error correction ability.
2Quantity of substance
If bad data columns are not detected and removed, then storage capacity is maximized, but error correction ability is consumed and reading/writing failures occur
Solution Approach 1:
The patent performs preliminary detection of bad data columns through write-read-compare operations before normal storage operations begin. By identifying and marking bad data columns in advance, the system prevents them from causing reading and writing failures during actual use, thus maintaining both storage capacity and operational reliability.
Solution Approach 2:
The patent implements feedback by comparing read data with write data to identify error bits, using this information to determine which columns are bad, and updating the bad data column markers accordingly. This feedback mechanism ensures that bad data columns are accurately identified and excluded from error correction resource consumption, preventing reading and writing failures while preserving storage capacity.
3Reliability
If error correction ability is increased to correct more errors, then more bad data columns can be tolerated, but storage capacity is reduced
Solution Approach 1:
The patent applies preliminary action by detecting and marking bad data columns before they consume error correction resources. The method performs write operations to test data columns, reads back the written data, compares it with the original write data to identify error bits, and marks columns with excessive error bits as bad data columns in advance. This prevents bad data columns from consuming error correction ability during normal operation, thereby resolving the contradiction between storage capacity and error correction ability.
Data Source
AI summary
A data storage device, and an error tolerance selecting method thereof which includes: writing data to data blocks of the data storage device; reading written data of the data blocks as read data; comparing the read data and the written data of each data column in the data blocks, and calculating a number of error bits in each chunk including a plurality of data columns accordingly; calculating a difference value between the number of error bits in the chunk and a first threshold value to store the difference value in an error tolerance list; and selecting a largest difference value in the error tolerance list as an error tolerance.