Storage Snapshot Tiering via Erasure Coding and Copy Offload
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Solution Overview
Problem
Existing data storage systems face challenges in efficiently managing data across multiple storage nodes and ensuring data integrity and availability, particularly in distributed storage clusters.
Innovation Solution
The implementation of a storage system that utilizes portable snapshot replication, where data is distributed across multiple storage nodes using erasure coding and redundant copies, managed by authorities that control data storage and retrieval processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is distributed across multiple storage nodes using erasure coding, then data availability and integrity are improved, but system complexity increases
Solution Approach 1:
The patent segments data into multiple chunks and distributes them across different storage nodes using erasure coding. This allows the system to maintain data availability even when some nodes fail, as the data can be reconstructed from the remaining chunks. The segmentation principle directly addresses the reliability improvement while managing complexity through structured data distribution.
Solution Approach 2:
The patent introduces authorities as intermediary components that manage data storage and retrieval operations across the distributed storage nodes. These authorities handle the complexity of erasure coding operations, node failure detection, and data reconstruction, thereby improving reliability while shielding the system from excessive complexity.
2Reliability
If redundant copies of data are maintained across storage nodes, then data integrity is improved, but storage space consumption increases
Solution Approach 1:
The patent creates redundant copies of data chunks across multiple storage nodes through erasure coding. Instead of storing complete duplicate copies, the system generates parity chunks that can be used to reconstruct lost data. This copying approach improves data integrity while optimizing storage space utilization compared to traditional replication methods.
Solution Approach 2:
The patent changes the parameter of data representation by transforming original data into encoded chunks and parity information through mathematical operations. This parameter transformation allows the system to maintain data integrity with less storage space than traditional redundancy methods, as the encoded form contains the necessary information for reconstruction without requiring full duplicate copies.
3Reliability
If proactive data rebuilding is implemented across storage nodes, then system reliability is improved, but processing time increases
Solution Approach 1:
The patent implements proactive data rebuilding by detecting node failures early and initiating reconstruction operations before data loss occurs. The system monitors storage node health and preemptively rebuilds data on alternative nodes, improving system reliability by preventing data loss scenarios while managing processing time through scheduled maintenance windows.
Solution Approach 2:
The patent maintains continuous data protection by implementing ongoing monitoring and reconstruction operations across the distributed storage system. The useful action of data protection continues uninterrupted through automated failure detection and reconstruction processes, ensuring system reliability while minimizing processing time impacts through efficient background operations.
Data Source
AI summary
Tiering snapshots across different storage tiers, including: creating a snapshot of a dataset, wherein the snapshot includes user data and metadata; offloading the snapshot of the dataset to a first storage level storage system; and migrating, in accordance with a lifecycle policy and via one or more copy offload operations, the snapshot from the first storage level storage system to a second storage level storage system.