Memory Sub-System Error Checking Data Generation
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Solution Overview
Problem
Conventional memory sub-systems cannot effectively detect errors introduced during data modification operations such as encryption, decryption, appending metadata, or truncation, as they lack the necessary error-checking data to validate the integrity of modified data.
Innovation Solution
The memory sub-system generates error-checking data at each modification step by combining the original error-checking data with data patterns or portions removed during these operations, allowing for incremental updates and error detection upon retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If error-checking data is generated only for original data, then storage simplicity is maintained, but error detection capability during modification operations is lost
Solution Approach 1:
The patent generates error-checking data in advance for both the original data and the modified data portions before the actual modification operation occurs. This preliminary generation of error-checking data enables subsequent error detection without adding complexity to the modification process itself, as the checking data is already prepared and stored alongside the data portions.
2Reliability
If error-checking data is updated after each modification, then data integrity is maintained, but processing time increases
Solution Approach 1:
The error-checking data for modified portions is generated in advance before the modification operation is executed. This allows the modification to proceed at full speed without waiting for error-checking data generation, while still ensuring data integrity can be verified afterward by comparing the pre-generated error-checking data with newly computed values.
3Reliability
If only original error-checking data is stored, then storage space is minimized, but verification of modified data is impossible
Solution Approach 1:
The patent divides the error-checking data into separate segments: one set for the original data portions and another set for the modified data portions. This segmentation allows the system to store only the necessary error-checking data for each segment independently, verifying modified data without requiring duplication of the entire error-checking data set, thus managing storage space efficiently while enabling verification.
Data Source
AI summary
First data is received. First error-checking data generated based on a cyclic redundancy check (CRC) operation of the first data is received. Second data is generated by combining the first data with a first data pattern. Second error-checking data of the second data is generated by using a combination of the first error-checking data and a second data pattern. The second data pattern has a size that is based on the first data pattern.