ABSTRACT
The Hirschberg algorithm is commonly used for protein sequence alignment, which is a very important task in bioinformatics. This article presents the AFMC framework for using the Hirschberg method to perform sequence alignment in multiple cloud computing services of different models, such as Infrastructure-as-a-Service and Function-as-a-Service (FaaS). Experiments were carried out in which several instances of AWS EC2, Azure VMs and Google Compute Engine as well as varied configurations of AWS Lambda, Azure Function, and Google Cloud Function were used to pairwise align COVID-19 spike proteins. The services were submitted to different levels of simultaneity to align the genetic sequences. The findings reveal that there is a tradeoff between predicted execution time and cost for this application, for example, FaaS-oriented cloud service models generally took less time to process the workloads. On the other hand, it was observed that, as the level of concurrence increased, there was a marked augmentation in cost. In this context, a framework that provides multi cloud solutions for bioinformatics such as AFMC is essential. © 2023 John Wiley & Sons, Ltd.