Replicated Storage Integrity Testing via Granular Hash Signatures
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Solution Overview
Problem
Conventional data protection systems face challenges in efficiently testing the integrity of replicated storage, particularly in snapshot shipping modes, where maintaining snapshots for long periods is resource-intensive and time-consuming, especially when dealing with large volumes of data.
Innovation Solution
The method involves generating coarse and fine granularity hash signatures for data areas in a snapshot volume, with course signatures sent for unchanged areas and fine signatures for changed areas to a replica site, allowing for integrity checking without requiring prolonged snapshot retention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If snapshots are retained for long periods to enable integrity testing of replicated storage, then data integrity can be verified, but memory space requirements increase and resources are consumed
Solution Approach 1:
The patent segments the snapshot volume into multiple areas and processes each area independently. Hash signatures are generated for individual areas rather than the entire volume, allowing selective integrity checking of only those areas that have changed. This segmentation enables the system to verify data integrity without retaining complete snapshots of the entire volume for extended periods.
Solution Approach 2:
The patent extracts only the necessary portions of snapshot data for integrity testing. By identifying and processing only the changed areas rather than the entire snapshot volume, the system extracts minimal required data for verification purposes. This extraction approach reduces memory space requirements while maintaining the ability to verify data integrity.
2Reliability
If complete snapshot volumes are processed for integrity testing, then comprehensive data verification is achieved, but processing time increases and productivity decreases
Solution Approach 1:
The patent applies local quality by differentiating between changed and unchanged areas of the snapshot volume. Instead of uniformly processing the entire volume, the system applies intensive integrity checking (fine granularity hash signatures) only to changed areas while using coarser checking or skipping unchanged areas. This localized approach maintains comprehensive verification of modified data while significantly reducing overall processing time.
Solution Approach 2:
The patent implements partial action by performing integrity testing on only the necessary portions of the snapshot volume—specifically, the changed areas. Rather than applying excessive action to the entire volume, the system applies verification resources proportionally to the actual changes, thereby achieving effective data protection without the performance penalty of processing unchanged data.
3Measurement precision
If fine granularity hash signatures are generated for all areas, then detailed integrity checking is achieved, but computational overhead and time consumption increase
Solution Approach 1:
The patent implements a dynamic integrity checking approach where the granularity of hash signature generation adapts based on the area being processed. For changed areas, fine granularity hash signatures are generated to provide detailed integrity verification. For unchanged areas, coarser checking or skipping is applied. This dynamic adjustment of verification intensity maintains measurement precision where needed while reducing overall processing time.
Solution Approach 2:
The patent changes the parameter of hash signature granularity based on the processing context. Fine granularity hash signatures are used for changed areas requiring detailed verification, while coarser approaches are used for unchanged areas. This parameter change strategy allows the system to maintain high measurement precision for critical areas while minimizing computational overhead and processing time across the entire volume.
Data Source
AI summary
In one aspect, a method includes marking a list of locations currently being shipped to a replica site, generating course granularity hash signatures of data for each area of memory in the snapshot volume, generating fine granularity hash signatures of data for each subarea of memory in the snapshot volume, sending course granularity hash signatures to the replica site for each area not being changed in a production volume and sending fine granularity hash signatures to the replica site for each area being changed in the production volume. The snapshot volume is a snapshot of the production volume.