TCHAO: parallelism with transaction classification and grouping by historical access objects to scale blockchain - Bin Yu; He Zhao; Tong Zhou; Lei Chen; Yuhui Fan (Journal of King Saud University: Computer and Information Sciences)
Abstract Blockchain technology has witnessed remarkable growth, especially with the advent of Ethereum and its smart contract capabilities, spurring widespread applications across diverse industries. However, the scalability issue remains a significant bottleneck, primarily due to the prevalent serial transaction execution approach in many blockchain systems, leading to high latency and low throughput. Deterministic parallelism and optimistic parallelism are currently the two types of excellent parallel schemes to improve transaction execution efficiency. But there are still some problems and challenges in parallel execution. To address these challenges, this paper presents a novel parallel execution model TCHAO, which leverages historical access objects to classify and group transactions. It allows for serial execution within groups and parallel execution between groups, thereby reducing transaction execution time. The model eliminates the need for pre-defining read–write sets or pre-executing transactions, which are common limitations in existing parallelism schemes. Through the implementation of a prototype system and comprehensive experiments, TCHAO demonstrates superior performance compared to SE (serial execution), EV (Execute-Validate) architecture and sharding schemes in terms of applicable blockchain types, throughput, latency, condition and limitation. This research provides a new perspective and solution for enhancing the scalability of blockchain systems.