Dispersed Storage Task Execution Using Encoded Data Slices
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Solution Overview
Problem
Current distributed storage and task processing systems face challenges in efficiently managing large data sets and complex tasks across multiple devices, particularly in ensuring data integrity and security, and in handling failures without loss of data or performance.
Innovation Solution
A distributed computing system that employs dispersed error encoding and decoding, allowing data to be stored and processed across multiple geographically dispersed units, using error correction schemes to ensure data integrity and security, and enabling fault tolerance by distributing data into encoded slices that can be reconstructed from any subset meeting a decode threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is distributed across multiple geographically dispersed units, then fault tolerance and data availability are improved, but system complexity and difficulty of managing data integrity increase
Solution Approach 1:
The system segments data into multiple encoded slices using dispersal encoding, distributing them across different geographically dispersed storage units. This segmentation enables fault tolerance since the original data can be reconstructed from any sufficient subset of slices, directly resolving the contradiction by improving reliability while managing complexity through systematic encoding.
Solution Approach 2:
The patent introduces encoded slices as intermediaries between the original data and the distributed storage units. These encoded slices act as mediators that carry the necessary information to reconstruct the original data, simplifying the management of distributed data while maintaining fault tolerance across geographically dispersed units.
2Reliability
If data is encoded and distributed into slices across multiple units, then data security and fault tolerance are improved, but data reconstruction complexity and processing time increase
Solution Approach 1:
The system performs preliminary dispersal encoding of data into slices before distribution, preparing the data structure in advance. This preliminary action ensures that when reconstruction is needed, the encoded slices are already in the correct format and can be quickly reassembled, reducing reconstruction time while maintaining data integrity.
Solution Approach 2:
The patent employs parameter changes in the dispersal encoding process, where the encoding parameters are optimized to balance data integrity with reconstruction speed. By adjusting encoding parameters, the system achieves both high data integrity and efficient reconstruction, resolving the contradiction between reliability and time loss.
3Reliability
If dispersed error encoding is used across multiple storage units, then data security and fault tolerance are improved, but computational overhead and processing complexity increase
Solution Approach 1:
The dispersal encoding and decoding processes are designed to be self-service, where the encoded slices themselves contain all necessary information for reconstruction without requiring complex external coordination. Each storage unit independently stores encoded slices that can be self-sufficiently combined to reconstruct the original data, reducing processing complexity while maintaining fault tolerance.
Data Source
AI summary
A method begins by a dispersed storage (DS) processing module selecting a set of distributed storage and task (DST) execution units for executing a task and determining dispersed storage error coding parameters for data. The method continues with the DS processing module dispersed storage error encoding the data in accordance with the parameters to produce a plurality of encoded data blocks and grouping the plurality of encoded data blocks into a plurality of encoded data block groupings. The method continues with the DS processing module partitioning the task into a set of partial tasks, outputting at least some of the plurality of encoded data block groupings to the set of DST execution units, and outputting the set of partial tasks to the set of DST execution units for execution of the set of partial tasks on the at least some of plurality of encoded data block groupings.