Blockchain Transaction Sharding Algorithm Based on Account-Weighted Graph

Abstract

Sharding technology is widely regarded as an effective way to solve blockchain scalability limitations, such as lower throughput and longer delay time. However, sharding encounters challenges related to high cross-shard transaction proportion and complex cross-shard transaction verification. Therefore, a transaction sharding algorithm based on account-weighted graph is proposed. Firstly, an account-based transaction sharding model is established from the viewpoint of data sharding. Secondly, based on this model, an account-weighted graph is constructed with accounts as nodes and transaction frequency between accounts as weights for the long-term accumulated transaction data of blockchain. The community discovery algorithm is adopted, and the accounts with the largest modularity gain are selected and merged according to the association relationship between the accounts, so a multi-shard blockchain is formed initially. Finally, the multi-shard blockchain is adjusted and rebuilt by splitting and merging. The proposed algorithm is compared with the modular sharding algorithm and the random sharding algorithm under the sharding granularity of 10. The cross-shard transaction proportion is reduced by 78.8% and 78.7%, the average cross-shard transaction delay of accounts is reduced by 36.1% and 44.5%, and the transaction throughput is increased by 93.1% and 122.1%. Under the other sharding granularities, the proposed algorithm also outperforms the two algorithms in terms of cross-shard transaction proportion and account transaction delay. In conclusion, this method effectively reduces the cross-shard transaction proportion and minimizes cross-shard transaction delay.

Keywords

• Scalability
• transaction sharding
• sharding granularity
• cross-shard transaction proportion
• transaction delay