Hash-Based Error Detection in Data Storage Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data storage systems rely on lightweight error detection techniques like single bit parity checks, which fail to detect multi-bit errors and are inadequate for noisy channels, leading to undetected read errors and reduced data integrity.
Innovation Solution
The use of a hash value generated from a Murmur hash function, stored during data write operations, for robust error detection by comparing it with a generated hash value during read operations, allowing for quick and reliable error detection and correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If lightweight error detection techniques such as single bit parity checks are used, then the implementation is easy and processing is fast, but multi-bit errors cannot be detected and data integrity is reduced
Solution Approach 1:
The patent changes the parameter of error detection from simple parity bits to hash values generated by Murmur hash functions. This parameter change enables detection of multi-bit errors while maintaining computational efficiency through optimized hashing algorithms designed for speed.
Solution Approach 2:
The patent substitutes the mechanical parity check system with a hash-based error detection system. Instead of using simple XOR operations on parity bits, the system uses Murmur hash functions to generate and verify hash values, providing superior error detection capability without significant performance penalty.
2Reliability
If robust error detection techniques are implemented, then data integrity is improved, but processing overhead and delays increase
Solution Approach 1:
The patent selects hash value lengths that balance detection robustness with processing speed. By optimizing the hash parameter size, the system achieves strong error detection capability while minimizing the computational time required for hash generation and verification.
Solution Approach 2:
The patent replaces traditional heavy-weight error detection mechanisms with optimized hash functions that provide comparable or superior detection capability at lower computational cost, thereby reducing processing delays while maintaining data integrity.
3Reliability
If hash values are generated and stored during write operations, then error detection capability is enhanced, but storage overhead increases
Solution Approach 1:
The patent optimizes the hash value length parameter to achieve an optimal balance between error detection robustness and storage overhead. By carefully selecting the hash size, the system ensures sufficient detection capability while minimizing the additional storage requirements.
Solution Approach 2:
The patent stores hash values as compact digital representations alongside the data. These hash copies serve as error detection tokens that require minimal storage space compared to the actual data, enabling efficient verification without significant overhead.
4Productivity
If lightweight parity checks are used in drive systems, then processing is fast, but errors from noisy channels such as electromagnetic interference cannot be detected
Solution Approach 1:
The patent substitutes traditional parity check systems with hash-based verification systems that are specifically designed to detect errors caused by noisy channels and electromagnetic interference. The Murmur hash functions provide robust error detection while maintaining processing efficiency.
Solution Approach 2:
The patent changes the error detection parameter from simple parity bits to optimized hash values that are specifically designed to detect bit flips and corruption caused by electromagnetic interference and noisy channels, while maintaining fast processing speeds.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Data processing methods and apparatus for processing stored data with error correcting bits to detect and in some instances correct errors. The data processing including, e.g., techniques such as the detection of errors by comparing hash values of data retrieved from storage with hash values of the data generated during storage. For example, one embodiment of a method in accordance with the present invention includes reading data stored with error correcting bits from a storage device, performing a hash operation on the data read from the storage device to generate a first hash value, comparing said first hash value to a previously generated hash value corresponding to said data, and determining that a read error has occurred when said first hash value does not match said previously generated hash value. In some embodiments, the method further includes performing an error recovery operation upon detection of an error.