A Responsive Knapsack-Based Algorithm for Resource Provisioning and Scheduling of Scientific Workflows in Clouds

Abstract

Scientific workflows are used to process vast amounts of data and to conduct large-scale experiments and simulations. They are time consuming and resource intensive applications that benefit from running in distributed platforms. In particular, scientific workflows can greatly leverage the ease-of-access, affordability, and scalability offered by cloud computing. To achieve this, innovative and efficient ways of orchestrating the workflow tasks and managing the compute resources in a cost-conscious manner need to be developed. We propose an adaptive, resource provisioning and scheduling algorithm for scientific workflows deployed in Infrastructure as a Service clouds. Our algorithm was desig..