Dispersed Storage Network Data Slice Migration
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Solution Overview
Problem
Existing dispersed storage networks face challenges in efficiently managing and migrating data across incremental storage resources, particularly in maintaining data integrity and availability when storage units fail or are added, without relying on redundant copies.
Innovation Solution
The implementation of a dispersed storage network (DSN) with a managing unit, integrity processing unit, and decentralized agreement module, which uses error encoding and decoding techniques like Cauchy Reed-Solomon encoding to distribute data across multiple storage units, allowing for data recovery and migration without loss, even in the presence of failures, by creating and managing encoded data slices and their storage across geographically diverse locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored using traditional redundant copying methods, then data availability is improved, but storage efficiency deteriorates due to duplicate data occupying additional space
Solution Approach 1:
The patent segments data into multiple slices and disperses them across different storage units using error encoding. Instead of creating redundant copies of entire data blocks, the system divides data into segments (slices) and distributes them across multiple storage units, allowing data to be reconstructed from any sufficient subset of slices. This segmentation approach maintains data availability while eliminating the need for complete redundant copies.
Solution Approach 2:
The patent changes the storage parameter from binary redundancy (copy or no copy) to distributed error-corrected encoding. By transforming data into encoded slices with specific redundancy properties, the system allows flexible reconstruction thresholds. The parameter change enables the system to achieve high availability with less total storage by using mathematical encoding rather than simple duplication.
2Productivity
If data is migrated across storage units in a dispersed storage network, then storage resource utilization is improved, but data integrity risks worsen during the migration process
Solution Approach 1:
The patent applies preliminary error encoding to data before migration begins. By pre-encoding data into error-corrected slices with built-in integrity checks, the system prepares the data to withstand potential corruption during migration. The preliminary encoding action ensures that even if some slices are corrupted or lost during transfer, the original data can be reconstructed from the remaining valid slices.
Solution Approach 2:
The patent implements feedback mechanisms through integrity verification during migration. The system continuously monitors the integrity of data slices during the migration process and can trigger re-transmission or error correction procedures. This feedback loop ensures that data integrity is maintained throughout the migration, allowing high productivity without sacrificing reliability.
3Quantity of substance
If incremental storage resources are added to the network, then storage capacity is improved, but system complexity worsens due to data migration and rebalancing requirements
Solution Approach 1:
The patent implements dynamic load balancing that automatically adapts to changing storage resources. When incremental storage resources are added, the system dynamically recalculates optimal data slice distribution and initiates targeted migrations. This dynamic approach allows the system to scale capacity while managing complexity through automated, adaptive algorithms rather than static, manual configurations.
Solution Approach 2:
The patent enables the dispersed storage network to self-manage data migration when resources change. The system automatically detects added storage units, determines optimal data redistribution patterns, and executes migrations without external intervention. This self-service capability reduces system complexity by eliminating the need for manual management of capacity expansion while maintaining optimal data distribution.
4Reliability
If error encoding techniques are used to distribute data across storage units, then data security is improved, but processing overhead worsens during encoding and decoding operations
Solution Approach 1:
The patent performs error encoding as a preliminary action during the initial data ingestion phase. By encoding data into error-corrected slices before distribution, the system pays the processing overhead once during ingestion rather than repeatedly during every access operation. This preliminary encoding maintains strong data security while minimizing time loss during subsequent read and write operations.
Data Source
AI summary
A method for execution by a computing device includes detecting that an incremental storage cohort has been added to a storage generation to produce an updated plurality of storage cohorts of an updated storage generation, where each storage cohort includes a set of storage units. For each storage cohort, a slice listing process is initiated to identify a plurality of DSN addresses associated with storage of data objects within the each storage cohort. For each DSN address, ranked scoring information is obtained for the each storage cohort of the updated plurality of storage cohorts. One storage cohort is identified based on the ranked scoring information. When the identified storage cohort is different than another storage cohort associated with current storage of encoded data slices associated with the DSN address of the identified storage cohort, a migration process is initiated to migrate the encoded data slices to the identified storage cohort.