Downsampling and Transparent Coding for Blockchain
This addresses storage and scalability problems for blockchain systems, though it appears incremental as it builds on existing coding techniques like fountain codes.
The paper tackles blockchain scalability issues caused by large historical data by proposing a downsampling method that reduces node storage overhead while maintaining node independence through entropy-based sampling, and demonstrates that the entire blockchain history can be efficiently recovered via cooperative decoding similar to fountain codes when reserved data follows a soliton distribution.
With the development of blockchain, the huge history data limits the scalability of the blockchain. This paper proposes to downsample these data to reduce the storage overhead of nodes. These nodes keep good independency, if downsampling follows the entropy of blockchain. Moreover, it demonstrates that the entire blockchain history can be efficiently recovered through the cooperative decoding of a group of nodes like fountain codes, if reserved data over these nodes obey the soliton distribution. However, these data on nodes are uncoded (transparent). Thus, the proposed algorithm not only keeps decentralization and security, but also has good scalability in independency and recovery.