A Storage Optimization Scheme for Blockchain Transaction Databases

As the typical peer-to-peer distributed networks, blockchain systems require each node to copy a complete transaction database, so as to ensure new transactions can by verified independently. In a blockchain system (e.g., bitcoin system), the node does not rely on any central organization, and every node keeps an entire copy of the transaction database. However, this feature determines that the size of blockchain transaction database is growing rapidly. Therefore, with the continuous system operations, the node memory also needs to be expanded to support the system running. Especially in the big data era, the increasing network traffic will lead to faster transaction growth rate. This paper analyzes blockchain transaction databases and proposes a storage optimization scheme. The proposed scheme divides blockchain transaction database into cold zone and hot zone using expiration recognition method based on Least Recently Used (LRU) algorithm. It can achieve storage optimization by moving unspent transaction outputs outside the in-memory transaction databases. We present the theoretical analysis on the optimization method to validate the effectiveness. Extensive experiments show our proposed method outperforms the current mechanism for the blockchain transaction databases.

Automated summary

Blockchain systems require nodes to copy a complete transaction database, leading to continuous database growth and the need to expand node memory. This paper proposes a storage optimization scheme based on the LRU algorithm, dividing transaction databases into cold and hot zones to optimize storage by moving unused transaction outputs out of memory. The proposed method outperforms current mechanisms for blockchain transaction databases, as supported by theoretical analyses and extensive experiments.