Encoded Slice Rebuild Scheduling in Dispersed Storage Networks
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Solution Overview
Problem
Current dispersed storage networks face challenges in securely and reliably storing data across multiple geographically distributed storage units, particularly in maintaining data integrity and security against unauthorized access and storage unit failures without the need for redundant copies.
Innovation Solution
A dispersed storage network (DSN) architecture that employs error encoding using Cauchy Reed-Solomon encoding, where data is segmented and encoded into multiple slices, stored across multiple storage units, and managed by a managing unit and integrity processing unit, enabling secure and reliable storage and retrieval with error correction capabilities.
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. Instead of storing complete redundant copies, the system divides data into fragments (slice 1, slice 2, slice 3, etc.) and stores them distributed across the network, achieving fault tolerance without requiring full duplicate storage.
Solution Approach 2:
The patent transforms data from its original form into encoded representations using error correction codes. By changing the parameter representation of data through mathematical encoding, the system enables recovery of original data from a subset of encoded slices, eliminating the need for storing multiple complete copies.
2Object-affected harmful factors
If data is dispersed across multiple storage units, then security against unauthorized access is improved, but system complexity increases due to distributed management
Solution Approach 1:
The patent segments both data and management functions. Data is divided into slices stored across multiple units, and management is divided into specialized components: DST clients for data operations, DST managers for coordination, and integrity processing units for verification. This segmentation distributes complexity across manageable specialized components.
Solution Approach 2:
The patent introduces intermediary components that facilitate secure distributed management. DST managers act as intermediaries between clients and storage units, coordinating operations and managing access. Integrity processing units serve as intermediaries for verifying data integrity, reducing the management burden on individual storage units.
3Reliability
If error correction encoding is applied to data, then data integrity is improved, but processing time increases during encoding and decoding operations
Solution Approach 1:
The patent applies error correction encoding in advance during the data writing phase. By performing the encoding operation before data is dispersed and stored, the system prepares corrected data representations upfront, so that during retrieval only decoding is needed, reducing the time penalty to half the total encode-decode cycle.
Solution Approach 2:
The patent implements partial error correction by requiring only a subset of slices for data recovery rather than all slices. This partial action approach reduces the decoding complexity and time required, as the system can reconstruct data from fewer encoded slices rather than processing the complete set.
4Reliability
If redundant copies of data are stored, then fault tolerance is improved, but storage capacity utilization deteriorates
Solution Approach 1:
The patent transforms data into encoded form where the relationship between stored slices and original data changes from direct copying to mathematical representation. This parameter change enables the system to store fewer slices than traditional redundancy would require, improving capacity utilization while maintaining fault tolerance through error correction properties.
Data Source
AI summary
A processing system associated with a dispersed storage network is configured to detect a plurality of encoded data slices to be rebuilt, wherein the plurality of encoded data slices are associated with the DST execution unit; identify a plurality of slice names associated with the plurality of encoded data slices; obtain a slice name to slice memory device mapping for the DST execution unit; determine a schedule of rebuilding the plurality of encoded data slices, based on the mapping; and facilitate rebuilding the plurality of encoded data slices in accordance with the schedule of rebuilding.