Computational resource and cost prediction service for scientific workflows in federated clouds

The use of cloud platforms has been widely encouraged in applications that require a lot of processing power and storage such as scientific workflows. However, users who operate such workflows are faced with a very large variety and quantity of available resources, specially considering cloud federation platforms, making difficult to choose efficiently. Thus, the design issue to operate such workflows is far from trivial resulting in a problem to scientific workflows' users. In order to address this problem, we propose a provisioning service called CRCPs - Computational Resource and Cost Prediction service that measure user resources and report the runtime financial cost before starting the workflow execution. In addition, CRCPs allows users to choose between high-performance, low-budget executions, or set how much to pay and how long to finish the workflow in an automatic and transparent way. The results show the CRCPs adequacy to estimate resources, time and execution cost of two different bioinformatic workflows executed using BioNimbuZ federated cloud platform. (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

The use of cloud platforms in scientific workflows presents challenges for users in selecting resources efficiently. To address this issue, a provisioning service called CRCPs is proposed to predict resource and cost, allowing users to optimize performance and budget before workflow execution. The results demonstrate the adequacy of CRCPs in estimating and optimizing resources, time, and cost.