Multi-Tier Dispersed Storage for Reliable Data Rebuilds
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Solution Overview
Problem
Current dispersed storage networks face challenges in efficiently managing and processing large datasets across distributed systems, particularly in ensuring data integrity and security, and in effectively allocating rebuilding tasks in the event of data corruption or loss.
Innovation Solution
A distributed computing system that employs dispersed error encoding and decoding schemes, allowing data to be segmented, encoded, and distributed across multiple storage units, with a task processing framework that enables parallel processing and secure data retrieval, and includes a rebuilding mechanism for corrupted or missing data slices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is distributed across multiple storage units using dispersed error encoding, then data reliability and fault tolerance are improved, but system complexity and management overhead increase
Solution Approach 1:
The patent segments data into multiple slices that are distributed across different storage units. Each slice is encoded using dispersed error encoding, allowing the system to reconstruct original data even if some slices are lost or corrupted. This segmentation approach directly improves data reliability while managing complexity through standardized encoding procedures.
Solution Approach 2:
The patent introduces a task allocation manager as an intermediary component that coordinates rebuilding tasks across distributed storage units. This manager receives rebuild requests, allocates tasks to appropriate storage units, and monitors completion, thereby reducing the management overhead complexity for distributed data reconstruction.
2Reliability
If rebuilding tasks are allocated across distributed storage units, then data recovery capability is improved, but task allocation complexity and processing time increase
Solution Approach 1:
The patent pre-allocates rebuilding tasks to storage units before actual data loss occurs. The task allocation manager maintains a ready pool of rebuilding tasks that can be immediately executed when data corruption is detected, eliminating the need for complex real-time task creation and allocation during recovery operations.
Solution Approach 2:
The patent allocates more storage units to rebuilding tasks than the minimum required for data reconstruction. This excessive allocation allows parallel processing of multiple rebuild operations simultaneously, reducing overall processing time despite increased initial task allocation complexity.
3Adaptability or versatility
If multiple storage types are integrated in a dispersed storage network, then storage versatility and capacity are improved, but data security and access management become more difficult
Solution Approach 1:
The patent creates a universal interface layer that handles data access requests regardless of the underlying storage type. The task allocation manager and encoding/decoding mechanisms work uniformly across different storage media (hard drives, solid-state drives, cloud storage), allowing the system to manage diverse storage types without increasing access management complexity for users.
Data Source
AI summary
A method includes receiving a write request to store a data object; identifying object parameters associated with the data object; selecting a memory type based on the identified object parameters; selecting a selected memory based on the memory type; and facilitating storage of the data object in the selected memory, wherein the data object is dispersed error encoded.