A Generic Framework for Optimization in Blockchain Simulators
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866913977203687424 |
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| author | Long, Hou-Wan Pan, Yujun Zhao, Xiongfei Si, Yain-Whar |
| author_facet | Long, Hou-Wan Pan, Yujun Zhao, Xiongfei Si, Yain-Whar |
| contents | As blockchain technology rapidly evolves, researchers face a significant challenge due to diverse and non-standardized simulation parameters, which hinder the replicability and comparability of research methodologies. This paper introduces a Generic Framework for Optimization in Blockchain Simulators (GFOBS), a comprehensive and adaptable solution designed to standardize and optimize blockchain simulations. GFOBS provides a flexible platform that supports various optimization algorithms, variables, and objectives, thereby catering to a wide range of blockchain research needs. The paper's key contributions are threefold: the development of GFOBS as a versatile tool for blockchain simulation optimization; the introduction of an innovative optimization method using warm starting technique; and the proposition of a novel concurrent multiprocessing technique for simultaneous simulation processes. These advancements collectively enhance the efficiency, replicability, and standardization of blockchain simulation experiments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_04157 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Generic Framework for Optimization in Blockchain Simulators Long, Hou-Wan Pan, Yujun Zhao, Xiongfei Si, Yain-Whar Computational Engineering, Finance, and Science As blockchain technology rapidly evolves, researchers face a significant challenge due to diverse and non-standardized simulation parameters, which hinder the replicability and comparability of research methodologies. This paper introduces a Generic Framework for Optimization in Blockchain Simulators (GFOBS), a comprehensive and adaptable solution designed to standardize and optimize blockchain simulations. GFOBS provides a flexible platform that supports various optimization algorithms, variables, and objectives, thereby catering to a wide range of blockchain research needs. The paper's key contributions are threefold: the development of GFOBS as a versatile tool for blockchain simulation optimization; the introduction of an innovative optimization method using warm starting technique; and the proposition of a novel concurrent multiprocessing technique for simultaneous simulation processes. These advancements collectively enhance the efficiency, replicability, and standardization of blockchain simulation experiments. |
| title | A Generic Framework for Optimization in Blockchain Simulators |
| topic | Computational Engineering, Finance, and Science |
| url | https://arxiv.org/abs/2508.04157 |