Multilevel Media Defect Detection for Storage Data Recovery
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Solution Overview
Problem
Existing methods for identifying defective regions on storage media are inadequate as they fail to detect all defective regions and do not account for regions that become defective over time, leading to potential data loss.
Innovation Solution
A multilevel media defect detection system that performs multiple data decodes with parameter modifications, including zeroing out soft data and regenerating data from defective regions, and an offline detection and decode process to recover data from defective areas using modified parameters such as defect amplitude threshold, run length threshold, and programmable scalars.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single-level media defect detection is performed, then the detection process is simple and fast, but defective regions are not fully identified leading to data loss
Solution Approach 1:
The defect detection process is segmented into multiple levels: a first media defect detection that identifies obvious defective regions, and a second media defect detection that performs additional detection on regions surrounding the first defective regions. This segmentation allows the system to achieve comprehensive defect identification while managing complexity by dividing the detection into manageable stages with different detection thresholds and strategies.
Solution Approach 2:
The first media defect detection is performed as a preliminary action to identify obvious defective regions before conducting the more resource-intensive second detection. This preliminary identification allows the system to focus subsequent detection efforts on specific regions of interest, improving overall detection accuracy while optimizing resource allocation by avoiding unnecessary full-media scanning at the highest detection level.
2Productivity
If data is written to defective regions, then storage capacity is maximized, but data loss occurs due to undetected defects
Solution Approach 1:
The multilevel media defect detection is performed as a preliminary action before data is written to the storage medium. By identifying and marking defective regions in advance through multiple detection passes with different thresholds, the system prevents data from being written to problematic areas, thereby maintaining data integrity while maximizing the use of reliable storage capacity.
Solution Approach 2:
The system uses feedback from the first media defect detection to guide the second detection process. Defective regions identified in the first detection serve as input for expanding the detection scope to surrounding areas in the second detection. This feedback mechanism ensures that potentially problematic regions are thoroughly identified before data writing, preventing future data loss while optimizing storage utilization.
3Reliability
If defective regions are marked as unusable, then data loss is prevented, but storage capacity is reduced and regions becoming defective over time are not identified
Solution Approach 1:
The detection process segments defective regions into different categories based on detection confidence and location. The first media defect detection identifies certain defective regions, while the second detection identifies additional regions surrounding the first. This segmentation allows the system to apply different strategies: confidently marking clearly defective regions as unusable while investigating borderline regions further, thereby protecting data while minimizing unnecessary capacity loss.
Solution Approach 2:
The system dynamically adjusts detection sensitivity and scope based on findings from previous detection stages. The second media defect detection operates with expanded parameters around regions identified by the first detection, allowing the system to adaptively investigate potential defects rather than applying a static, overly conservative threshold that would unnecessarily reduce storage capacity.
Data Source
AI summary
Various embodiments of the present invention provide systems and methods for deriving data from a defective media region. As an example, a method for deriving data from a defective media region is disclosed that includes providing a storage medium and performing a media defect detection that indicates a defective region on the storage medium. A first data decode is performed on data corresponding to the defective region. The first data decode yields a first output. It is determined that the first output failed to converge and based at least in part on the failure of the first output to converge, a second data decode is performed on the data corresponding to the defective region. The second data decode includes zeroing out any soft data corresponding to the defective region and providing a second output.