Floating Data Protection Scheme for Storage Tier Transitions
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Solution Overview
Problem
Current data storage systems face inefficiencies when changing protection schemes for data, as it requires resource-intensive re-protection and adds complexity with multi-tiered storage, especially when moving less valuable data to lower-tiered storage.
Innovation Solution
The implementation of a floating data protection scheme that allows for the reduction of coding fragments by discarding unnecessary ones, enabling a change from a higher to a lower protection scheme without re-protection, using a coding matrix to maintain data integrity and avoid single points of failure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data re-protection is performed when changing from expensive to cheaper protection schemes, then data protection reliability is maintained, but system resource consumption increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and validating the target protection scheme before actually transitioning data. The system verifies that the cheaper protection scheme meets durability requirements in advance, preventing unnecessary re-protection operations and reducing resource consumption during data migration between storage tiers.
Solution Approach 2:
The patent implements feedback mechanisms by continuously monitoring data access patterns, value changes, and protection scheme effectiveness. This feedback loop allows the system to dynamically adjust protection levels and avoid unnecessary re-protection operations, optimizing the balance between reliability and resource consumption.
2Productivity
If multi-tiered storage is implemented to manage different data values, then storage capacity utilization improves, but system complexity increases
Solution Approach 1:
The patent applies universality by creating a unified protection framework that works across multiple storage tiers simultaneously. The same protection scheme validation and transition mechanisms are used whether moving data between hot, warm, or cold storage, reducing the need for tier-specific complexity while maintaining optimal storage capacity utilization.
Solution Approach 2:
The patent uses parameter changes by dynamically adjusting protection levels based on data value, access patterns, and storage tier characteristics. Rather than implementing complex multi-tiered management, the system changes protection parameters (encoding schemes, redundancy levels) according to data characteristics, simplifying the overall system architecture while improving storage utilization.
3Reliability
If protection scheme changes are performed frequently to match data value changes, then data protection optimality improves, but operation time increases
Solution Approach 1:
The patent applies periodic action by implementing scheduled reviews of data protection schemes based on data age, access patterns, and value changes. Rather than continuously monitoring and adjusting protection levels, the system performs periodic assessments and batch transitions, reducing operational overhead and time loss while maintaining protection optimality.
Solution Approach 2:
The patent uses preliminary action by pre-validating protection scheme transitions and preparing target storage configurations before actual data migration. This advance preparation reduces the time required for protection scheme changes by eliminating runtime validation and adjustment operations.
Data Source
AI summary
Floating data protection is presented herein. The method comprises receiving a defined data protection policy; determining that the defined data protection policy is not susceptible to a single point of failure scenario; and in response to determining that the defined data protection policy is not susceptible to the single point of failure scenario, reducing a code fragment associated with a data portion based on the defined data protection policy.