Dispersed Storage Vault Synchronization via Erasure Coding
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Solution Overview
Problem
Current dispersed storage networks face challenges in maintaining data integrity and security across geographically distributed storage units, particularly in handling errors and failures without redundant copies, while ensuring secure and indefinite data storage.
Innovation Solution
The implementation of a dispersed storage network (DSN) with error encoding using Cauchy Reed-Solomon encoding, where data is segmented into encoded data slices stored across multiple sites, allowing for error correction and secure data retrieval without the need for redundant copies, utilizing a managing unit and integrity processing unit to manage and rebuild 'bad' or missing slices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored using traditional redundant copying methods, then data reliability is improved, but storage efficiency deteriorates due to duplicate data occupying additional space
Solution Approach 1:
The patent segments data into multiple slices and distributes them across different storage units using information dispersal algorithms. Instead of storing complete redundant copies of data, the system divides data into N slices where any K slices can reconstruct the original data, achieving both reliability and storage efficiency.
Solution Approach 2:
The patent changes the fundamental parameter of data representation by using erasure coding parameters (N, K) instead of traditional replication factors. This allows flexible adjustment of the balance between reliability and storage efficiency by modifying the encoding parameters without changing the underlying storage architecture.
2Productivity
If data is dispersed across multiple geographically distributed storage units, then system availability is improved, but data integrity deteriorates due to increased exposure to errors and failures
Solution Approach 1:
The patent implements feedback mechanisms through checksums and cyclic redundancy checks (CRC) that are calculated and stored with each data slice. When data is retrieved or during storage operations, these checksums provide feedback to verify data integrity, allowing the system to detect and correct errors that occur during dispersal across multiple storage units.
Solution Approach 2:
The patent performs preliminary error detection and correction by embedding checksums and redundancy information into data slices before they are dispersed to storage units. This preliminary action ensures that even if corruption occurs during transmission or storage, the integrity can be verified and recovered without requiring retransmission from multiple sources.
3Reliability
If error correction codes are implemented in dispersed storage systems, then data security is improved, but computational complexity deteriorates due to encoding and decoding overhead
Solution Approach 1:
The patent applies partial error correction by implementing erasure coding that only adds the minimum necessary redundancy (K slices out of N total slices). This partial action approach provides sufficient security and reliability without the excessive computational overhead of full redundancy, allowing the system to tolerate up to N-K failures while maintaining reasonable encoding and decoding complexity.
Data Source
AI summary
A method for execution by one or more processing modules of one or more computing devices of a dispersed storage network (DSN). The method begins by receiving a data access requests with regards to a data object. The method continues by identifying a vault set based on the data access request, where a plurality of storage vaults includes the vault set. The method continues by obtaining configuration information associated with the vault set and determining whether to process the data access request based on the obtained configuration information associated with the vault set.