Blockchain Hierarchical Storage via Merkle Tree Pruning
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Solution Overview
Problem
Existing blockchain-based storage systems face challenges in efficiently managing and pruning historical state data, leading to difficulties in hierarchical storage due to complex reusing relationships between nodes on Merkle trees, which hinders accurate data migration and storage optimization.
Innovation Solution
A blockchain-based hierarchical storage method and apparatus that organizes account state data into a state Merkle tree, labels each node with a block number indicating the update block, and implements a migration threshold to migrate nodes from higher to lower level storage based on block number intervals, allowing for precise pruning and hierarchical storage by removing historical data from the Merkle tree.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all historical state data nodes are retained in the Merkle tree for complete data preservation, then data completeness and reliability are improved, but storage costs and system complexity increase significantly
Solution Approach 1:
The patent segments the storage of state data nodes by introducing level identifiers that categorize nodes into different storage levels based on their block number ranges. This allows the system to divide historical data into manageable segments that can be stored at different hierarchical levels, optimizing both accessibility and storage efficiency.
Solution Approach 2:
The patent changes the parameter of node identification by adding level identifiers to existing node hashes. This parameter change enables the system to distinguish between different storage levels without altering the fundamental node structure, allowing for efficient data migration and pruning while maintaining data integrity.
2Quantity of substance
If historical state data is pruned from the Merkle tree to reduce storage costs, then storage efficiency is improved, but data retrieval complexity and potential loss of historical information increase
Solution Approach 1:
The patent performs preliminary actions by pre-calculating and storing level identifiers with each state data node before migration occurs. This preliminary tagging enables the system to automatically determine which nodes should be migrated to lower storage levels without requiring complex analysis during the migration process, simplifying data management.
Solution Approach 2:
The patent creates copies of state data nodes with additional level identifier information while maintaining the original node structure. This copying approach allows the system to preserve the integrity of original nodes while adding hierarchical classification, enabling efficient pruning without losing access to historical data through the copy-reference mechanism.
3Device complexity
If a simple storage structure is used for state data, then system complexity is reduced, but the ability to efficiently manage and migrate historical data decreases
Solution Approach 1:
The patent implements a nested structure by embedding level identifier information within the existing node hash structure. This nesting approach allows the system to maintain a relatively simple external interface while incorporating sophisticated hierarchical management capabilities inside, enabling efficient data migration without significantly increasing overall system complexity.
Data Source
AI summary
Disclosed herein are methods, systems, and apparatus, including computer programs encoded on computer storage media, for blockchain-based hierarchical data storage. One of the methods includes: determining, based on a blockchain stored in a database that includes multiple levels of storage, a block number interval that includes one or more block numbers associated with data nodes to be migrated to a lower level of storage in response to the data nodes meeting a data migration condition, wherein each of the data nodes is included in a state Merkle tree and is associated with a block number of a block of the blockchain where the corresponding data node was last updated, and the lower level of storage corresponds to a storage media with lower storage cost.