Blockchain Data Storage With ECC for Low-Volume Node Replication
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Solution Overview
Problem
Distributed ledger systems (DLSs) face challenges in reducing storage space on nodes while maintaining data equality and processing efficiency, as they store entire copies of large blockchain data, leading to 'data inequality' and inefficient use of resources.
Innovation Solution
Implementing error correction coding (ECC) on blockchain nodes to identify infrequently visited blocks, encode them, divide the encoded blocks into data sets, hash and store hash values, and delete the original data sets, allowing nodes to store only a portion of the encoded data and retrieve the rest from other nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If every node stores an entire copy of the blockchain, then data equality is maintained, but storage space consumption increases significantly
Solution Approach 1:
The blockchain data is segmented into frequently visited blocks and infrequently visited blocks. Nodes store complete copies of frequently visited blocks locally, while infrequently visited blocks are stored remotely. This segmentation allows nodes to maintain data equality for frequently accessed data while reducing overall storage space consumption.
Solution Approach 2:
Different storage strategies are applied to different parts of the blockchain data based on their access patterns. Frequently visited blocks receive local storage with high availability, while infrequently visited blocks use remote storage. This local quality approach optimizes the balance between storage space and data accessibility.
2Quantity of substance
If a few shared nodes store the entire copy of the blockchain, then storage space is reduced for individual nodes, but data inequality is created
Solution Approach 1:
Multiple nodes are combined into a distributed remote storage system that collectively stores infrequently visited blocks. Instead of relying on a single shared node, the system merges the storage capabilities of multiple nodes to provide redundant, equal-access storage for all participants, thereby maintaining data equality while reducing individual storage requirements.
3Quantity of substance
If old block data or state data are not frequently visited, then storage space can be reduced, but data retrieval capability must be maintained
Solution Approach 1:
The system performs preliminary actions by pre-storing infrequently visited blocks in remote storage with their hash values cached locally. When data retrieval is needed, the system can quickly verify data integrity using the pre-stored hash values and fetch the actual data from remote storage, maintaining ease of operation despite reduced local storage.
Solution Approach 2:
Hash values serve as intermediaries between the locally stored data structures and the remotely stored block data. The hash values enable efficient verification and retrieval of remote data without requiring the full block data to be stored locally, thus maintaining data retrieval capability while reducing storage space.
Data Source
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AI summary
Disclosed herein are methods, systems, and apparatus, including computer programs encoded on computer storage media, for storing blockchain data. One of the methods includes determining, by a blockchain node, one or more blocks that are infrequently visited; performing error correction coding of the one or more blocks to generate one or more encoded blocks; dividing, based on one or more predetermined rules, each of the one or more encoded blocks to a plurality of data sets; selecting one or more data sets from the plurality of data sets of each of the one or more encoded blocks based on the one or more predetermined rules; hashing the one or more data sets to generate one or more hash values corresponding to the one or more data sets; storing the one or more hash values; and deleting the one or more data sets.