Identifying Information Requirement for Scheduling Kepler Workflow in the Cloud

Abstract

Kepler scientific workflow system has been used to support scientists to automatically perform experiments of various domains in distributed computing systems. An execution of a workflow in Kepler is controlled by a director assigned in the workflow. However, users still need to specify compute resources on which the tasks in the workflow are executed. To further ease the technical effort required by scientists, a workflow scheduler that is able to assign workflow tasks to resources for execution is necessary. To this end, we identify from a review of several cloud workflow scheduling techniques the information that should be made available in order for a scheduler to schedule Kepler workflow in the cloud computing context. To justify the usefulness, we discuss each type of information regarding workflow tasks, cloud resources, and cloud providers based on their benefit on workflow scheduling.