Comparative Analysis of Scientific Workflow Scheduling Algorithms in Cloud Under Budget Constraint

Abstract

Due to the popularity of Cloud services, most of the scientists executing their applications such as workflows on these virtual resources. So scheduling of scientific workflows under QoS constraint in a cloud environment is the most recent research topic. There is a number of algorithms have been proposed to schedule scientific workflows to minimize makespan while meeting budget constraint. As per our analysis, we do not find any survey paper available in the literature that analyzes the performance of different workflow scheduling algorithms in the cloud under a budget constraint. In this paper, we have considered most recent workflow scheduling algorithms such as StarScale, BHEFT, HBCS, and conducted a comparative analysis in detail. According to our analysis, result shows that HBCS algorithm provides the maximum variation in cost and makespan when the budget is varied. Whereas BHEFT produces a moderate variation in results and ScaleStar produces almost no variation in results.