Tree-Based Slice Storage in DSNs for Recovery Without Full Copies
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current dispersed storage networks face challenges in ensuring data integrity and availability due to storage unit failures, requiring robust error encoding and decoding mechanisms to prevent data loss without redundant copies.
Innovation Solution
A dispersed storage network (DSN) employing Cauchy Reed-Solomon error encoding and decoding, where data is segmented into encoded data slices stored across multiple geographically distributed units, allowing for data recovery with a decode threshold, and utilizing an integrity processing unit to rebuild 'bad' or missing slices.
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 distributes them across different storage units. Instead of storing complete redundant copies of entire files, the system divides data into smaller segments (slices) that can be independently stored and retrieved. This segmentation allows the system to achieve data availability through distributed storage while improving storage efficiency by avoiding complete duplication of all data across multiple locations.
Solution Approach 2:
The patent implements a hierarchical storage structure where metadata trees and data trees are nested within each other. The metadata tree contains information about data slices, while the data tree contains the actual encoded data slices. This nested structure allows efficient organization and retrieval of data without requiring complete redundant copies at each level, thereby improving storage efficiency while maintaining data availability.
2Reliability
If error correction codes are applied to protect against data corruption, then data integrity is improved, but computational complexity deteriorates due to encoding and decoding operations
Solution Approach 1:
The patent applies error correction encoding to data slices during the initial storage process, before the data is actually stored in the distributed network. By performing the encoding operation in advance (preliminary action), the system ensures data integrity is built into the stored slices, eliminating the need for complex real-time encoding during write operations. The encoded slices are then directly stored and can be reliably retrieved and decoded only when necessary for data reconstruction.
Data Source
AI summary
A method for execution by a dispersed storage and task (DST) execution unit includes receiving a slice write request via a network that includes a data slice and extracting metadata from the data slice. The metadata is stored in a metadata storage tree in a first memory device of the DST execution unit and the data slice is stored in a slice storage tree in a second memory device of the DST execution unit based on tree utilization parameters.