Dispersed Storage Node Access for Fault-Tolerant Media Data
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Solution Overview
Problem
Current distributed storage and task processing systems face challenges in efficiently managing and processing large datasets across multiple geographically dispersed locations, particularly in ensuring data integrity and availability while handling complex tasks, and balancing load distribution effectively.
Innovation Solution
A distributed computing system that employs dispersed error encoding and decoding schemes, allowing data to be segmented, encoded, and distributed across multiple execution units for storage and processing, with a network architecture that supports secure, reliable, and scalable data storage and task execution, using a distributed storage and task network (DSTN) module to manage and coordinate data partitioning, encoding, and task distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is distributed across multiple geographically dispersed locations, then data availability and fault tolerance are improved, but system complexity and coordination overhead increase
Solution Approach 1:
The patent segments data into multiple slices and distributes them across different storage nodes geographically. Each slice is independently stored and can be accessed, allowing the system to maintain high availability while managing complexity through modular data organization rather than monolithic distribution
Solution Approach 2:
The patent introduces a distributed storage manager as an intermediary component that coordinates data placement, retrieval, and fault recovery across geographically dispersed nodes. This mediator abstracts the complexity of distributed coordination from individual nodes, centralizing management functions while maintaining distribution benefits
2Reliability
If data is encoded and segmented across multiple nodes, then fault tolerance is improved, but access time and processing complexity increase
Solution Approach 1:
The patent performs preliminary data encoding and segmentation into slices before distribution, pre-positioning data fragments across multiple nodes. This preliminary action ensures that when access is needed, the system can immediately retrieve required slices without performing complex real-time encoding or reconstruction operations
Solution Approach 2:
The patent implements fault tolerance by storing data across more nodes than strictly necessary for minimal redundancy. This excessive distribution ensures that even if multiple nodes fail, sufficient copies remain available for quick retrieval, trading some additional access overhead for significantly improved reliability
3Productivity
If load is balanced across multiple execution units, then system scalability is improved, but coordination overhead and communication requirements increase
Solution Approach 1:
The patent creates execution units with universal capabilities that can process any type of computational task assigned to them. Each execution unit is designed to be functionally equivalent and interchangeable, allowing load to be balanced across units without requiring complex task-specific routing or coordination logic
Solution Approach 2:
The patent implements self-service mechanisms where execution units autonomously manage their own task execution and state without requiring constant coordination with central controllers. Each unit can independently process assigned workloads and report status, reducing coordination overhead while maintaining balanced load distribution across the scalable system
Data Source
AI summary
A method begins by a dispersed storage (DS) processing module receiving data objects from a plurality of authorized users and determining a system level storage efficiency preference for a data object. The method continues with the DS processing module selecting a set of storage nodes of an on-line media storage system based on the system level storage efficiency preference and determining dispersed storage error encoding parameters. The method continues with the DS processing module encoding the data object in accordance with the dispersed storage error encoding parameters to produce encoded data slices and generating system addressing information. The method continues with the DS processing module storing the encoded data slices in the set of storage nodes using the system addressing information and updating a user profile for the authorized user to include the system addressing information.