Logical Corruption Detection in Persistent Storage via Mirror Site Recovery
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Solution Overview
Problem
Legacy storage systems fail to detect logical corruption in persistent storage devices, leading to potential complete data loss, especially in scenarios where data is written once and read infrequently, such as in backup or archival systems, as existing disk scrubbing technologies cannot recognize logically corrupted blocks until they cause read errors.
Innovation Solution
A method and system that utilize multiple mirror sites to detect and recover from logical corruption by receiving a trigger event, retrieving uncorrupted data from alternate locations, comparing it to determine match values, and writing good data to the corrupted site before performing consistency checks on blocks in physical or logical proximity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If disk scrubbing is implemented to detect bad blocks, then detection capability is improved, but it cannot recognize logically corrupted blocks until read errors occur
Solution Approach 1:
The patent performs consistency checks on mirror site data before using it for recovery. By preliminarily verifying the integrity of mirror copies through checksums or other validation mechanisms, the system ensures that recovered data is not logically corrupted, preventing propagation of undetected corruptions while maintaining proactive detection capabilities.
Solution Approach 2:
The patent introduces an intermediary consistency check mechanism between the disk scrubbing process and the data recovery process. This intermediary layer validates the logical integrity of data blocks and mirror copies, allowing the system to detect logical corruptions that traditional disk scrubbing would miss until read errors occurred.
2Productivity
If data is written once and read infrequently (backup/archival scenario), then storage efficiency is improved, but latent corruption goes undetected for long periods
Solution Approach 1:
The patent implements periodic consistency checks on mirror site data even in write-once read-infrequently scenarios. By scheduling regular validation of mirror copies and performing proactive recovery operations, the system detects latent corruptions before they cause data loss, addressing the detection delay problem while maintaining storage efficiency through targeted rather than continuous operations.
3Reliability
If mirror sites are used for recovery, then data recovery capability is improved, but system complexity increases
Solution Approach 1:
The patent uses mirror site copies of data blocks to restore corrupted data. By maintaining simplified duplicate copies of critical data at mirror sites and implementing straightforward copy-and-validate recovery operations, the system achieves robust recovery capability without introducing complex error correction codes or sophisticated data reconstruction algorithms, thus managing system complexity effectively.
4Reliability
If automatic recovery is implemented, then system availability is improved, but processing overhead increases
Solution Approach 1:
The patent performs consistency checks and recovery operations locally at the storage device level using mirror site data. By implementing automatic recovery through local validation and restoration operations rather than requiring centralized coordination or extensive data movement, the system achieves improved availability while minimizing processing overhead and energy consumption.
Data Source
AI summary
A method, system, and computer program product for restoring blocks of data stored at a corrupted data site using two or more mirror sites. The method commences by receiving a trigger event from a component within an application server environment where the trigger event indicates detection of a corrupted data site. The trigger is classified into at least one of a plurality of trigger event types, which trigger event type signals further processing for retrieving from at least two mirror sites, a first stored data block and a second stored data block corresponding to the same logical block identifier from the first mirror site. The retrieved blocks are compared to determine a match value, and when the match value is greater than a confidence threshold, then writing good data to the corrupted data site before performing consistency checks on blocks in physical or logical proximity to the corrupted data site.