Error-Encoded Data Ingestion for Fault-Tolerant Distributed Storage
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Solution Overview
Problem
Existing data storage and processing systems face challenges in efficiently managing large volumes of data across distributed networks, particularly in ensuring data integrity and security while handling complex tasks, and are vulnerable to failures without 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 security, and enabling efficient task execution with tolerance to failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in a dispersed storage network across multiple locations, then data security and fault tolerance are improved, but system complexity and coordination overhead increase
Solution Approach 1:
The patent segments data into multiple slices that are distributed across different storage locations in the network. Each slice is independently stored and can be retrieved, allowing the system to achieve fault tolerance and security without requiring complex centralized coordination mechanisms.
Solution Approach 2:
The patent introduces a data slice selector as an intermediary component that manages the selection and retrieval of data slices. This intermediary abstracts the complexity of distributed data management, providing a simplified interface for data access while maintaining the benefits of dispersed storage.
2Productivity
If data is processed and forwarded amongst multiple computing devices, then processing capacity and reliability are improved, but communication overhead and latency increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing data at the source device and preparing data slices for distribution before actual processing needs occur. This reduces the communication overhead during active processing, as data is already in the required format and location.
Solution Approach 2:
The patent implements dynamic data forwarding where data slices are routed to computing devices based on current processing needs and device availability. This dynamic approach optimizes communication paths and reduces latency by adapting to real-time system conditions rather than following fixed routing patterns.
Data Source
AI summary
A method for execution by one or more computing devices of a massive data ingestion system, the method includes retrieving a data segment from a cache memory of the massive data ingestion system. The method further includes error encoding, in accordance with error encoding parameters, the data segment to produce a set of encoded data slices, where the error encoding parameters include a pillar width number and a decode threshold number, and where the decode threshold number is a minimum number of encoded data slices needed to reconstruct the data segment. The method further includes storing the set of encoded data slices in a set of storage units of the massive data ingestion system.