Deadline and cost based workflow scheduling in hybrid cloud

Abstract

Cloud computing provides on demand resources for compute and storage requirements. Private cloud is a good option for cost saving for executing workflow applications but when the resources in private cloud are not enough to meet storage and compute requirements of an application then public clouds are the option left. While public clouds charge users on pay-per-use basis, private clouds are owned by users and can be utilized with no charge. When a public cloud and a private cloud is merged, we get a hybrid cloud. In hybrid cloud, task scheduling is a complex process as jobs can be allocated resources either from private cloud or from public cloud. Deadline based scheduling is the main focus in many of the workflow applications. Proposed algorithm does cost optimization by deciding which resources should be taken on lease from public cloud to complete the workflow execution within deadline. In the proposed work, we have developed a level based scheduling algorithm which executes tasks level wise and it uses the concept of sub-deadline which is helpful in finding best resources on public cloud for cost saving and also completes workflow execution within deadlines. Performance analysis and comparison of the proposed algorithm with min-min approach is also presented.