Storage Network Memory Selection for Dispersed Data Slices
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Solution Overview
Problem
Existing data storage and processing systems face challenges in efficiently managing and securing large volumes of data across distributed networks, particularly in ensuring data integrity and availability in the face of failures without the need for redundant copies.
Innovation Solution
A distributed computing system that employs dispersed storage and task processing units, utilizing error encoding and decoding techniques to store and process data across geographically diverse locations, ensuring data integrity and availability through redundant encoding and secure retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored using traditional redundant copying methods, then data availability is improved, but storage efficiency deteriorates due to duplicate data occupying additional space
Solution Approach 1:
The patent segments data into multiple slices and disperses them across different storage locations. Instead of storing complete redundant copies, the system divides data into fragments that can be reassembled from any sufficient subset, thereby reducing total storage requirements while maintaining availability.
Solution Approach 2:
The patent transforms data from its original form into encoded representations using error correction coding. This parameter transformation allows the system to store data in a compressed, encoded state that requires less space than traditional redundancy while enabling recovery of original data through decoding operations.
2Reliability
If data is dispersed across multiple storage locations, then fault tolerance is improved, but system complexity increases due to distributed management
Solution Approach 1:
The patent implements self-healing capabilities where the distributed storage system automatically detects, locates, and repairs corrupted or missing data slices without external intervention. The error correction coding enables the system to autonomously reconstruct lost data from remaining slices, reducing operational complexity.
Solution Approach 2:
The system incorporates continuous monitoring and feedback mechanisms that track the status of dispersed data slices across storage locations. This feedback enables dynamic adjustment of data placement and automatic initiation of repair operations when issues are detected, simplifying distributed management through automated control loops.
3Reliability
If error correction coding is applied to data, then data integrity is improved, but processing time increases due to encoding and decoding operations
Solution Approach 1:
The patent applies error correction encoding to data before dispersal and storage, performing the computationally intensive encoding operation in advance rather than during retrieval. This preliminary action ensures data integrity is established upfront, allowing faster retrieval operations since decoding can proceed in parallel with data reconstruction.
Solution Approach 2:
The system recovers data from a subset of available slices rather than requiring all slices for reconstruction. By designing the error correction code with a threshold property, the system performs partial recovery operations using only the necessary number of slices, reducing processing time while maintaining full data integrity.
4Object-affected harmful factors
If data is encrypted for security, then security against hacking is improved, but access speed deteriorates due to decryption requirements
Solution Approach 1:
The patent encrypts data in segmented form across multiple slices rather than encrypting complete data blocks. This segmentation allows selective decryption of only the necessary slices for a given operation, reducing the total decryption workload and improving access speed while maintaining security through distributed encryption.
Data Source
AI summary
A processing system of a storage network operates by: selecting a queue memory type of a plurality of memory types to store a data object, based on a size parameter associated with the data object; storing the data object in a queue memory device having the queue memory type, when the queue memory type is selected; selecting a main memory type of a plurality of memory types to store the data object, when the queue memory type is not selected; and storing the data object in a main memory device having the main memory type, when the queue memory type is not selected; wherein the data object is dispersed error encoded and stored as a plurality of encoded data slices.