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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| Format: | Article |
| Language: | English |
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Springer
2025-06-01
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| 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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| _version_ | 1849234360274780160 |
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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 |
| record_format | Article |
| 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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