Nowadays, more and more computer-based scientific experiments need to handle massive
amounts of data. Their data processing consists of multiple computational steps and …

Data lakes are a fundamental building block for many industrial data analysis solutions and
becoming increasingly popular in research. Often associated with big data use cases, data …

In the last years, scientific workflows have emerged as a fundamental abstraction for
structuring and executing scientific experiments in computational environments. Scientific …

Scientists have many computing infrastructures available to conduct their research,
including grids and public or private clouds. This article explores the use of these cyber …

Data analysis is an exploratory process that demands high performance computing (HPC).
SciPhylomics, for example, is a data-intensive workflow that aims at producing …

In this paper, we propose BeeFlow-an in situ analysis enabled workflow management
system across multiple platforms using Docker containers. BeeFlow can support both …

For the development of a predictive autoscaler for private clouds, an evaluation method was
needed. A survey of available tools was made, but none were found suitable. The …

The big data era is here, a natural result of the digital revolution of the last few decades. The
emergence of big data in virtually all areas of life raises a fundamental question-how can we …

Cloud computing and Internet of Things (IoT) are emerging technologies that have
experienced rapid development in recent years. While cloud computing presents a new …

Scientific experiments can be modeled as Workflows. Such Workflows are usually
computing-and data-intensive, demanding the use of High-Performance Computing …