Distributed Storage Segmentation for Fault Tolerance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current distributed storage and task processing systems face challenges in ensuring data integrity and efficient task execution across geographically dispersed storage units, particularly in handling large datasets and complex tasks, due to limitations in error correction and data slicing mechanisms.
Innovation Solution
The system employs a distributed computing architecture that uses dispersed error encoding and decoding techniques, segmenting data into slices and pillars, and distributing them across multiple execution units for secure storage and parallel processing, with mechanisms for error detection and reconstruction to ensure data integrity and efficient task execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is segmented into slices and distributed across multiple storage units, then data reliability and fault tolerance are improved, but system complexity and overhead increase
Solution Approach 1:
The patent segments data into multiple slices and distributes them across different storage units, enabling fault tolerance and reliability improvement while managing system complexity through structured segmentation
Solution Approach 2:
The patent introduces intermediary components including slicing modules, encoding modules, and coordination mechanisms that manage the complexity of distributed data storage and retrieval operations
2Reliability
If error correction encoding is applied to data slices, then data integrity is improved, but processing time and computational overhead increase
Solution Approach 1:
The patent applies error correction encoding in advance during data ingestion and storage, so that when data retrieval occurs, the integrity protection is already in place, reducing real-time processing delays
Solution Approach 2:
The patent adjusts error correction parameters and encoding schemes based on data priorities and storage conditions, optimizing the balance between integrity assurance and processing efficiency
3Reliability
If data is stored in dispersed locations across multiple units, then fault tolerance is improved, but data retrieval efficiency decreases
Solution Approach 1:
The patent segments data into distributed slices that can be independently accessed and retrieved in parallel from multiple storage units, improving both fault tolerance and retrieval efficiency
Solution Approach 2:
The patent combines retrieval operations by coordinating access to multiple data slices across dispersed storage units, enabling parallel processing and reducing overall retrieval time while maintaining fault tolerance
4Productivity
If complex task processing is distributed across multiple execution units, then processing capacity is improved, but coordination overhead and communication costs increase
Solution Approach 1:
The patent segments complex tasks into smaller sub-tasks that can be independently executed by multiple distributed execution units, increasing processing capacity while managing coordination through structured task division
Solution Approach 2:
The patent employs universal coordination mechanisms and standardized interfaces that enable multiple execution units to work together efficiently, reducing communication overhead and simplifying task distribution across the distributed system
Data Source
AI summary
A method begins by receiving data to be distributedly stored in a storage network and continues by determining a decode threshold value for storage of the data, wherein the data is to be distributedly stored in the storage network. The method continues by determining a preferred encoded data slice size for storage of the data, where the preferred encoded data slice size is based on a minimum performance level requirement and based on the preferred encoded data slice size and the decode threshold value the method continues by determining a preferred segment size for the data. The method then continues by determining a segmentation scheme for the data based on the preferred segment size for the data and segmenting the data into a plurality of data segments in accordance with the segmentation scheme. The method then continues by determining dispersed error encoding parameters for encoding each data segment and encoding each data segment to produce a set of error encoded data slices.