| Autor: |
Seungwoo Jung, Yeonho Yoo, Gyeongsik Yang, Chuck Yoo |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
ICT Express, Vol 10, Iss 6, Pp 1253-1258 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2405-9595 |
| DOI: |
10.1016/j.icte.2024.09.003 |
| Popis: |
Blockchain is increasingly offered as blockchain-as-a-service (BaaS) by cloud service providers. However, configuring BaaS appropriately for optimal performance and reliability resorts to try-and-error. A key challenge is that BaaS is often perceived as a “black-box,” leading to uncertainties in performance and resource provisioning. Previous studies attempted to address this challenge; however, the impacts of both vertical and horizontal scaling remain elusive. To this end, we present machine learning-based models to predict network reliability and throughput based on scaling configurations. In our evaluation, the models exhibit prediction errors of ∼1.9%, which is highly accurate and can be applied in the real-world. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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