Dynamic Hash Comparison for Content Addressable Storage Replication
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Solution Overview
Problem
Current data storage systems lack efficiency in replication processes between content addressable storage systems, as they treat all data similarly without considering replication scenarios, leading to suboptimal communication and increased complexity.
Innovation Solution
The system optimizes replication sessions by analyzing replication statistics to dynamically modify hash comparison methods, allowing for efficient data transfer by bypassing unnecessary steps in the replication process, such as shortening hash comparisons for duplicate data and switching between replication modes based on data overlap, thereby improving replication efficiency and reducing latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional replication methods are used that treat all data similarly, then data transfer completeness is ensured, but replication efficiency deteriorates and time consumption increases
Solution Approach 1:
The patent applies local quality by differentiating hash comparison methods based on data characteristics. Different replication scenarios (new data, updated data, duplicate data) use different hash comparison strategies, allowing each data type to be processed with the most appropriate method rather than a uniform approach.
Solution Approach 2:
The system dynamically adjusts hash comparison length and methodology based on replication scenario analysis. The hash comparison process transitions from fixed-length to variable-length comparisons, and from synchronous to asynchronous models, optimizing performance for each specific replication context.
2Reliability
If full hash comparisons are performed for all data, then data accuracy is maintained, but I/O operations increase and system performance deteriorates
Solution Approach 1:
The patent implements partial action by performing only the necessary portion of hash comparisons. For duplicate data detected through short hash matches, full hash verification is skipped entirely. For unique data, full hash comparisons are performed to ensure accuracy. This selective approach maintains reliability where needed while improving overall system performance.
3Productivity
If replication sessions process all data uniformly, then completeness is ensured, but bandwidth utilization deteriorates and unnecessary operations increase
Solution Approach 1:
The system extracts and identifies duplicate data through short hash comparisons before initiating full replication. By taking out duplicate data from the replication pipeline early in the process, unnecessary bandwidth consumption is eliminated while ensuring complete replication of only the necessary data portions.
4Adaptability or versatility
If complex replication scenarios are handled with fixed processing methods, then system simplicity is maintained, but adaptability deteriorates and optimization is limited
Solution Approach 1:
The patent segments the replication process into distinct phases: short hash comparison, scenario analysis, and conditional full hash comparison or direct replication. This segmentation allows the system to handle multiple replication scenarios through a structured yet flexible framework that balances adaptability with manageable complexity.
Data Source
AI summary
A system, computer program product, and computer-executable method for managing replication from a production site to a target site, wherein both the production site and the target site are content addressable data storage systems, the system, computer program product, and computer-executable method including processing a replication session from the production site to the target site, collecting information related to the replication session from the production site to the target site, analyzing the information to determine whether to change the processing of the replication session, upon a positive determination, modifying the processing of the replication session.