Re-Encoding Data in Expanded Storage Pool
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Solution Overview
Problem
Existing technologies face challenges in efficiently storing and retrieving error-encoded data across a dispersed storage network, particularly in ensuring data integrity and availability in the presence of failures.
Innovation Solution
The implementation of a distributed storage network (DSN) that uses error correction schemes to encode data, allowing for the storage and retrieval of data slices across multiple storage units while maintaining data integrity and availability through error decoding and rebuilding of missing slices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is dispersed across multiple storage units in a DSN, then data availability and fault tolerance are improved, but system complexity increases
Solution Approach 1:
The patent segments data into multiple encoded slices that are distributed across different storage units in the DSN. Each slice is independently stored, allowing the system to tolerate failures while maintaining data availability. The segmentation is achieved through error correction coding that divides the original data into multiple redundant pieces.
Solution Approach 2:
The patent introduces a DSN controller as an intermediary that manages the complex operations of encoding, distributing, and retrieving data across the dispersed storage network. The controller handles the complexity of coordinate encoding, slice distribution, and reconstruction, shielding users from the underlying system complexity while maintaining high reliability.
2Reliability
If error correction schemes are implemented across the DSN, then data integrity is improved, but processing time and computational resources increase
Solution Approach 1:
The patent applies error correction encoding in advance during the data writing phase, creating redundant encoded slices that are immediately distributed across the DSN. This preliminary action ensures data integrity is built into the storage structure itself, so that when retrieval occurs, the error correction overhead is minimal and processing time is reduced.
Solution Approach 2:
The patent uses coordinate encoding that transforms data into a different parameter space where error correction becomes more efficient. By changing the representation of data through mathematical transformation, the system achieves robust error correction with optimized processing requirements during both write and read operations.
3Quantity of substance
If additional storage units are added to expand the DSN, then storage capacity is improved, but data redistribution and re-encoding complexity increases
Solution Approach 1:
The patent implements a dynamic DSN architecture where the encoding parameters and slice distribution can be adaptively adjusted when storage capacity changes. When new storage units are added, the system dynamically re-encodes and redistributes data using updated coordinate systems, allowing seamless capacity expansion without manual intervention or complex static reconfiguration.
Solution Approach 2:
The patent creates a universal encoding framework that works regardless of the number or configuration of storage units. The coordinate encoding system is designed to be scalable and adaptable to different DSN topologies, allowing the same fundamental approach to handle both initial data distribution and subsequent expansions without requiring fundamentally different mechanisms.
Data Source
AI summary
A processing system is operable to encode data to produce a first set of data slices based on a value of a width parameter. The data is stored based on maintaining storage of the first set of data slices across a set of storage units of a storage pool. Storage of the first set of data slices is maintained in the set of storage units of the storage pool after addition of an additional set of storage units added to the storage pool. The value of the width parameter is increased to an increased value to produce an updated width parameter. The data is re-encoded in accordance with the updated width parameter to produce a second set of data slices. The data is re-stored based on maintaining storage of the second set of data slices across the expanded set of storage units of the storage pool.


