Authors: Seungwoo Jung, Yeonho Yoo, Gyeongsik Yang, Chuck Yoo
Venue: ICT Express, JCR 2023 IF 4.1 Top 23.1% Volume 10, Issue 6, December 2024, pp. 1253-1258, doi: 10.1016/j.icte.2024.09.003. (2024)
Abstract: 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.