Sector Signature Patterns for Detecting Write Loss in Data Storage
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Solution Overview
Problem
Data storage systems face challenges in detecting lost writes and inconsistencies, as existing error detection and correction mechanisms are ineffective against these types of errors, leading to potential data corruption.
Innovation Solution
Implementing a sector signature transition controller that uses a plurality of sector signature patterns, including horizontal and diagonal parity values, to embed and update data signatures, and performs data integrity checks using metadata records and pattern-to-key lookups, allowing for efficient detection and correction of data integrity errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional error detection and correction codes (EDAC) are used to detect bit flips and sector failures, then data integrity against these errors is improved, but lost writes and inconsistencies remain undetected
Solution Approach 1:
The patent segments data into slices and assigns sector signatures to specific sectors within each slice. This segmentation allows the system to track writes at the sector level while maintaining slice-level integrity checks, enabling detection of lost writes that traditional EDAC cannot detect.
Solution Approach 2:
The patent introduces sector signatures as an intermediary mechanism between the data storage system and error detection. These signatures act as a mediator that tracks sector-level changes and enables detection of lost writes, bridging the gap between traditional EDAC and comprehensive data integrity verification.
2Reliability
If sector signature patterns are embedded with every data slice to enable integrity checks, then detection of lost writes is improved, but computational burden and system complexity increase
Solution Approach 1:
The patent applies partial action by performing integrity checks only on sectors that have been modified or are suspected of containing lost writes. Rather than checking every sector in every slice, the system selectively verifies sectors based on write operations and signature mismatches, reducing computational overhead while maintaining detection capability.
Solution Approach 2:
The patent changes parameters by using compact sector signature patterns (e.g., 16-bit or 32-bit values) instead of comprehensive checksums. This parameter change reduces the computational burden of generating and verifying signatures while maintaining sufficient discrimination capability to detect lost writes.
3Measurement precision
If multiple sector signature patterns are used to replace embedded patterns on writes, then detection accuracy is improved, but write operation overhead increases
Solution Approach 1:
The patent applies preliminary action by pre-generating and storing multiple sector signature patterns in advance. When a write operation occurs, the system can quickly select and apply the appropriate pre-computed signature without performing complex calculations during the write, thus maintaining high accuracy while minimizing write overhead.
Solution Approach 2:
The patent uses periodic action by cycling through a sequence of sector signature patterns for different writes to the same slice. This periodic pattern replacement provides comprehensive coverage over time, ensuring that lost writes are detected while distributing the computational load across multiple operations rather than concentrating it in a single expensive verification.
Data Source
AI summary
Sector signature patterns with sector signature values and sector signature parity values are embedded with data slices. A new pattern is embedded with a slice each time the slice data is updated. The patterns are selected in order such that every sector signature value and sector signature parity value changes when a new pattern is embedded. A separate metadata record such as a key is maintained to indicate which pattern has been embedded with the slice. A data integrity check is performed by comparing the embedded sector signature parity values with the metadata record and/or performing a pattern-to-key lookup.