Composable Transactions in Dispersed Storage Networks
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Solution Overview
Problem
Current computer networks face challenges in ensuring data integrity and availability across distributed storage systems, particularly in scenarios where multiple storage units are geographically dispersed, as they lack efficient error encoding and decoding mechanisms to handle data corruption and failures without redundant copies.
Innovation Solution
The implementation of a dispersed storage network (DSN) that uses error encoding techniques like Cauchy Reed-Solomon encoding to split data into encoded slices, which are then stored across multiple storage units, allowing for data recovery even if some slices are corrupted or missing, and enabling secure, long-term data storage without the need for redundant copies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored using traditional RAID systems or simple redundancy copies, then data availability is maintained, but storage efficiency decreases and device complexity increases
Solution Approach 1:
The patent segments data into multiple slices and applies error correction encoding to create encoded slices. These encoded slices are then distributed across multiple storage units. This segmentation approach allows the system to store data efficiently without requiring complete redundant copies, thereby maintaining data availability while reducing storage overhead and system complexity compared to traditional RAID systems.
2Reliability
If data is dispersed across geographically distributed storage units, then system reliability improves, but data integrity becomes more difficult to ensure
Solution Approach 1:
The patent applies error correction encoding to data slices before dispersing them across geographically distributed storage units. This preliminary encoding action ensures that even if some slices are corrupted or lost during transmission or storage, the original data can be reconstructed at the decoding stage, thereby maintaining data integrity while benefiting from the reliability improvements of geographic distribution.
3Reliability
If redundant copies of data are stored, then data recovery capability improves, but storage space consumption increases
Solution Approach 1:
The patent transforms the storage approach by applying error correction encoding parameters to data slices, converting them into encoded slices with different mathematical properties. This parameter transformation allows the system to achieve data recovery capability without storing complete redundant copies, as the encoded slices contain distributed information that can be reconstructed through decoding operations, thereby reducing storage space consumption while maintaining reliability.
Data Source
AI summary
A method for execution by a dispersed storage and task (DST) processing unit includes initializing a composite operation from a plurality of independent operations. An empty transaction context is created by performing an evaluation of the composite operation. A multi-source compare and swap (CASN) transaction is created from resulting expected values determined by evaluating the composite operation in the empty transaction context. The CASN transaction is executed against a dispersed storage network (DSN) memory. When the execution of the CASN transaction is successful, the transaction is committed to the DSN memory. When the execution failed due to at least one conflicting value stored in the DSN memory, a new transaction context pre-populated with the at least one conflicting value is created, and an updated CASN for the composite operation that utilizes the new transaction context is executed.