Workflows are an application model that enables the automated execution of multiple
interdependent and interconnected tasks. They are widely used by the scientific community …

The rapid growth of cloud computing in the last decade has led to an increasing concern
about the energy requirement of cloud data centers. Dynamic virtual machine (VM) …

Workflow scheduling in Heterogeneous Distributed Computing Environments (HDCEs) is a
NP-hard problem. Although a number of scheduling approaches have been proposed for …

Many resource management techniques for task scheduling, energy and carbon efficiency,
and cost optimization in workflows rely on a-priori task runtime knowledge. Building runtime …

In this survey, we discuss the challenges of executing scientific workflows as well as existing
Machine Learning (ML) techniques to alleviate those challenges. We provide the context …

The efficient prediction of cloud resource demand plays a crucial role in resource allocation
and scheduling in cloud data centers, helping to optimize resource utilization and improve …

Computing services are increasingly located in computing clouds, which allows for on-
demand scalability but may also increase operating costs. It is believed that cloud expenses …

Next generation software built for the cloud recently has embraced serverless computing
platforms that use temporary infrastructure to host microservices offering building blocks for …

Cloud computing is gaining popularity among small and medium-sized enterprises. The cost
of cloud resources plays a significant role for these companies and this is why cloud …

Many scientific workflow scheduling algorithms need to be informed about task runtimes a-
priori to conduct efficient scheduling. In heterogeneous cluster infrastructures, this problem …