TCHAO: parallelism with transaction classification and grouping by historical access objects to scale blockchain

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 seri...

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Main Authors: Bin Yu, He Zhao, Tong Zhou, Lei Chen, Yuhui Fan
Format: Article
Language:English
Published: Springer 2025-06-01
Series:Journal of King Saud University: Computer and Information Sciences
Subjects:
Online Access:https://doi.org/10.1007/s44443-025-00090-7
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author Bin Yu
He Zhao
Tong Zhou
Lei Chen
Yuhui Fan
author_facet Bin Yu
He Zhao
Tong Zhou
Lei Chen
Yuhui Fan
author_sort Bin Yu
collection DOAJ
description 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.
format Article
id doaj-art-022c85983fce46bcabf5ccacbf22be05
institution Kabale University
issn 1319-1578
2213-1248
language English
publishDate 2025-06-01
publisher Springer
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series Journal of King Saud University: Computer and Information Sciences
spelling doaj-art-022c85983fce46bcabf5ccacbf22be052025-08-20T04:03:11ZengSpringerJournal of King Saud University: Computer and Information Sciences1319-15782213-12482025-06-0137412010.1007/s44443-025-00090-7TCHAO: parallelism with transaction classification and grouping by historical access objects to scale blockchainBin Yu0He Zhao1Tong Zhou2Lei Chen3Yuhui Fan4Anhui Engineering Research Center for Agricultural Product Quality Safety Digital Intelligence, Fuyang Normal UniversityHefei Institutes of Physical Science, Chinese Academy of SciencesHefei Institutes of Physical Science, Chinese Academy of SciencesHuainan Normal UniversityHuainan Normal UniversityAbstract 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.https://doi.org/10.1007/s44443-025-00090-7BlockchainScalabilityParallelismTransaction classificationHistorical access objects
spellingShingle Bin Yu
He Zhao
Tong Zhou
Lei Chen
Yuhui Fan
TCHAO: parallelism with transaction classification and grouping by historical access objects to scale blockchain
Journal of King Saud University: Computer and Information Sciences
Blockchain
Scalability
Parallelism
Transaction classification
Historical access objects
title TCHAO: parallelism with transaction classification and grouping by historical access objects to scale blockchain
title_full TCHAO: parallelism with transaction classification and grouping by historical access objects to scale blockchain
title_fullStr TCHAO: parallelism with transaction classification and grouping by historical access objects to scale blockchain
title_full_unstemmed TCHAO: parallelism with transaction classification and grouping by historical access objects to scale blockchain
title_short TCHAO: parallelism with transaction classification and grouping by historical access objects to scale blockchain
title_sort tchao parallelism with transaction classification and grouping by historical access objects to scale blockchain
topic Blockchain
Scalability
Parallelism
Transaction classification
Historical access objects
url https://doi.org/10.1007/s44443-025-00090-7
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