Concurrent Data Stream Decoding for Time-Aligned Dispersed Storage
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Solution Overview
Problem
Current computer storage systems face challenges with data integrity and security due to the failure of memory devices, particularly those using physical movement technologies, such as disc drives, which can lead to bit-level corruption and require redundant arrays like RAID to ensure data availability but increase maintenance demands and security risks.
Innovation Solution
A distributed storage system that employs error coding dispersal storage, where data is partitioned into slices and encoded using forward error correction, allowing for reliable storage and retrieval across multiple geographically diverse locations, ensuring data integrity and security through redundancy without the need for extensive redundant arrays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If redundant arrays like RAID are used to ensure data availability, then data reliability is improved, but device complexity and maintenance demands increase
Solution Approach 1:
The patent segments data into multiple slices and distributes them across different storage locations. Error correction codes are applied to create redundant information that can recover from failures without requiring complex RAID arrays. This segmentation approach simplifies the storage system while maintaining reliability.
Solution Approach 2:
The patent introduces error correction codes as an intermediary mechanism between data and storage media. These codes act as a mediator that enables data recovery from corrupted or lost slices without requiring direct access to multiple redundant copies, thereby reducing system complexity and maintenance overhead.
2Reliability
If multiple redundant copies of data are stored, then data reliability is improved, but security risks increase due to multiple access points
Solution Approach 1:
The patent divides data into multiple encrypted slices distributed across different locations. Each slice alone is insufficient to reconstruct the original data, providing security against unauthorized access while maintaining reliability through error correction codes that enable recovery from legitimate failures.
Solution Approach 2:
The patent applies encryption transformations to data slices, changing their parameter state from readable to unreadable form. This ensures that even if multiple copies exist, unauthorized access is prevented while the error correction mechanism remains functional for authorized recovery.
3Reliability
If higher-grade disc drives are used to reduce failure rates, then data reliability is improved, but cost increases significantly
Solution Approach 1:
The patent employs error correction codes that enable reliable storage using standard, lower-cost storage media. By incorporating redundancy at the data level rather than requiring expensive hardware, the system achieves high reliability with commodity components, reducing overall system cost.
4Speed
If data is stored in centralized locations, then access efficiency is improved, but vulnerability to single points of failure increases
Solution Approach 1:
The patent segments data into distributed slices stored across multiple geographically separated locations. Error correction codes enable efficient reconstruction of original data from any sufficient subset of slices, providing both access efficiency and resistance to localized failures or disasters.
Data Source
AI summary
A method begins by a dispersed storage (DS) processing module receiving one or more pairs of coded values. The method continues with the DS processing module creating a received coded matrix from the one or more pairs of coded values. When the received coded matrix includes a decode threshold number of pairs of coded values, the method continues with the DS processing module generating a data matrix from the received coded matrix and an encoding matrix, reproducing a one of a first plurality of data segments from a first plurality of data blocks of the data matrix, and reproducing a one of a second plurality of data segments from a second plurality of data blocks of the data matrix, wherein the one of the first plurality of data segments and the one of the second plurality of data segments maintain the time alignment of a first and second data streams.