Dispersed Storage Retrieval Using Encoded Slice Mapping
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Solution Overview
Problem
Current distributed storage and task processing systems face challenges in efficiently managing and retrieving large amounts of data across geographically dispersed locations, particularly in ensuring data integrity and security while handling complex tasks, due to limitations in error correction and data distribution schemes.
Innovation Solution
A distributed computing system that employs dispersed storage error encoding and decoding techniques, where data is segmented, encoded, and distributed across multiple nodes, allowing for reliable storage and retrieval of data, and execution of tasks through a network of geographically dispersed execution units, with error correction mechanisms to ensure data integrity and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is distributed across multiple geographically dispersed nodes, then system reliability and fault tolerance are improved, but data retrieval efficiency and consistency are worsened
Solution Approach 1:
The patent segments data into multiple data objects that are distributed across different storage nodes. Each data object can be independently stored, retrieved, and managed, allowing the system to maintain high reliability through geographic distribution while improving retrieval efficiency by accessing only specific segments rather than entire datasets.
Solution Approach 2:
The patent introduces a distributed file system as an intermediary layer between users and the underlying storage nodes. This intermediary manages data location tracking, retrieval coordination, and reconstruction of original data from distributed segments, thereby maintaining retrieval efficiency despite geographic distribution.
2Reliability
If error correction encoding is applied to ensure data integrity, then data security and reliability are improved, but processing complexity and storage overhead are worsened
Solution Approach 1:
The patent applies error correction encoding in advance during the data writing phase, before data is distributed to storage nodes. By pre-encoding data with redundancy information, the system ensures data integrity can be verified and restored during retrieval without adding complex real-time processing overhead during data access operations.
3Adaptability or versatility
If data is segmented and distributed across multiple nodes, then system scalability and fault tolerance are improved, but data retrieval complexity and coordination overhead are worsened
Solution Approach 1:
The patent implements feedback mechanisms where storage nodes report data object location and status information back to the distributed file system. This feedback enables the system to track distributed data segments efficiently, manage retrieval operations, and maintain coordination overhead at manageable levels even as the system scales to numerous nodes.
Data Source
AI summary
A method includes identifying an independent data object of a plurality of independent data objects for retrieval from dispersed storage network (DSN) memory. The method further includes determining a mapping of the plurality of independent data objects into a data matrix, wherein the mapping is in accordance with the dispersed storage error encoding function. The method further includes identifying, based on the mapping, an encoded data slice of the set of encoded data slices corresponding to the independent data object. The method further includes sending a retrieval request to a storage unit of the DSN memory regarding the encoded data slice. When the encoded data slice is received, the method further includes decoding the encoding data slice in accordance with the dispersed storage error encoding function and the mapping to reproduce the independent data object.