Dispersed Storage Network Data Availability via Error Encoding
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Solution Overview
Problem
Current dispersed storage networks face challenges in maintaining data integrity and availability due to storage unit failures without redundant copies, and they struggle to efficiently manage and decode error-encoded data across geographically distributed storage units.
Innovation Solution
A dispersed storage network architecture that utilizes error encoding techniques like Cauchy Reed-Solomon encoding to split data into encoded slices, which are then stored across multiple geographically diverse storage units, allowing for data reconstruction even with partial failures, and includes a managing unit for vault creation, security, and resource allocation to ensure data integrity and availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is split into encoded slices and stored across multiple geographically diverse storage units, then data availability and reliability are improved during partial failures, but system complexity increases due to the need for error encoding and distributed management
Solution Approach 1:
The patent divides data into multiple encoded slices using error correction coding (e.g., Cauchy Reed-Solomon) and distributes these slices across geographically diverse storage units. This segmentation allows the system to tolerate partial failures while maintaining data availability, as sufficient slices can be retrieved and decoded even when some storage units are unavailable.
Solution Approach 2:
The patent introduces a managing unit that acts as an intermediary between clients and storage units. This managing unit handles vault creation, slice allocation, encoding/decoding operations, and coordination during data retrieval or reconstruction, thereby abstracting the complexity of distributed error-encoded storage from end users and simplifying system interaction.
2Reliability
If multiple storage units are used to store encoded data slices, then data integrity is improved through error correction, but the time required to decode and reconstruct data increases
Solution Approach 1:
The patent performs error correction encoding in advance during the data writing phase, organizing data into encoded slices and distributing them to storage units before any potential failure occurs. This preliminary encoding ensures that when data needs to be reconstructed from partial failures, the system only needs to retrieve and decode the necessary slices rather than performing complex error correction from scratch, thereby reducing reconstruction time.
3Reliability
If geographically diverse storage units are used, then resistance to localized failures is improved, but coordination and management difficulty increase
Solution Approach 1:
The managing unit serves multiple functions including vault creation, slice allocation across geographically diverse storage units, encoding and decoding operations, and coordination during data retrieval or reconstruction. By consolidating these diverse functions into a single multi-functional managing unit, the patent simplifies the overall system architecture and reduces management complexity despite the geographic distribution of storage units.
4Reliability
If error correction encoding is applied to data, then data protection is improved during storage failures, but storage space efficiency decreases due to increased data volume
Solution Approach 1:
The patent employs error correction encoding schemes such as Cauchy Reed-Solomon that allow flexible configuration of the number of encoded slices and the minimum number of slices required for reconstruction. By adjusting these parameters, the system can optimize the balance between data protection level and storage space efficiency according to specific requirements, enabling configurable trade-offs between reliability and storage capacity.
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 determining an addressing range of a storage configuration of the DSN. The method continues by determining a storage performance level associated with the addressing range. The method continues by determining whether the storage performance level compares favorably to a storage performance threshold. The method continues, when the storage performance level does not compare favorably to a storage performance threshold, by determining an updated storage configuration associated with the addressing range and re-assigning storage resources in accordance with the updated storage configuration.