Non-disruptive Mirror Consistency Check via Checksum Verification
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Solution Overview
Problem
Conventional mirroring and archival backup systems face challenges in ensuring the consistency of mirrored data sets due to errors from network, software, and physical media malfunctions, leading to data loss and disruption of backup operations, which can result in reduced effectiveness and increased time between backup operations, causing synchronization issues between source and destination storage systems.
Innovation Solution
A system and method for verifying the consistency of mirrored data sets between source and destination storage systems, implemented as a destination verification module cooperating with a source verification module, which sends version information, determines a base PCPI, generates and transmits a data stream with checksum information, and logs mismatches to correct inconsistencies, ensuring the destination storage system is consistent with the source.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional mirroring systems perform verification operations to ensure data consistency, then data reliability is improved, but backup operations are disrupted and time between backups increases
Solution Approach 1:
The system performs verification operations during idle periods or scheduled maintenance windows before actual backup operations are needed. Checksum validation and mirror consistency checks are executed in advance, so that when backup operations commence, the verification is already complete, thus improving data reliability without disrupting backup productivity
Solution Approach 2:
The invention introduces an intermediary verification layer that operates independently from the main backup workflow. A separate verification module compares checksums of source and destination data without interfering with the primary backup process, allowing both verification (improving reliability) and continuous backup operations (maintaining productivity) to occur simultaneously through this intermediary mechanism
2Measurement precision
If verification operations are performed to detect data errors, then data accuracy is improved, but system resources and time are consumed
Solution Approach 1:
Instead of verifying every single data block, the system performs partial verification by sampling key checksums at strategic points in the data set. This selective verification approach maintains high measurement precision for critical data while significantly reducing the total time and resources consumed compared to exhaustive verification of all data blocks
Solution Approach 2:
The verification operation is implemented as a periodic process rather than a continuous one. The system verifies data consistency at scheduled intervals using checksum comparisons, which provides sufficient measurement precision to detect errors while minimizing the cumulative time lost to verification operations by not continuously checking every data transfer
Data Source
AI summary
A system and method for verifying the consistency of mirrored data sets between source and destination storage systems is provided. A destination verification module sends version information to the source storage system where the source verification module determines whether the source and destination storage systems are utilizing compatible versions of the verification module. If the destination verification module receives an acceptable version from the source, the destination module then determines a base PCPI to utilize for verification and sends a PCPI identifier of the base PCPI to the source. The source verification module generates and transmits a data stream consisting of comprising of checksum information. The destination verification module compares the received data stream with checksum information retrieved from disk. If there are mismatches, i.e. the received data differs from the data retrieved from disk, the destination verification module logs the data mismatches in a verification log file.