Research on Scientific Workflow Scheduling Based on Budget Allocation in Cloud Environment

The scientific workflow deployment in the cloud environment is different from the traditional independent task scheduling,and the scheduling time and cost should be considered simultaneously.To address the problem,a scientific workflow scheduling method based on budget allocation is proposed.The mapping between workflow tasks and virtual machine resources is divided into two stages:budget allocation,and resource provision and scheduling.In order to optimize budget usage,a budget allocation algorithm based on fast-priority,called FFTD,and budget allocation algorithm based on slow-priority,called SFTD,are designed to achieve sub-allocation of budget among tasks.The task selection is performed based on the descending order of the earliest completion time of the task,and the resources are allocated according to the sub-budget of the single task when the virtual machine is reusable,thereby ensuring smooth scheduling of the workflow task.Five kinds of conventional types of scientific workflows are introduced to test the performance of the algorithm under different types of workflow structures and different budget constraints.The results show that the FFTD algorithm has shorter scheduling time and higher virtual machine resource utilization and satisfaction rate of budget constraints than the BDT-AI algorithm in 72%,88%and 84% experimental scenarios,and the overall performance is better.