A Deadline Constrained Scheduling Algorithm for Cloud Computing System based on the Timing Strategy

For the workflow scheduling question with delivery time constraints in cloud computing environments, a time-aware scheduling-driven cloud computing scheduling algorithm is proposed. This algorithm considers the impact of the workflow task path length on the overall workflow delivery time and introduces a sub-deadline allocation strategy. Additionally, a time-aware scheduling strategy is presented to address the cost reduction challenge of workflow execution under the pricing policies of cloud services. The sub-deadline allocation strategy assigns different sub-deadlines to cloud users based on the length of the workflow task path, ensuring compliance with user delivery time constraints while increasing the flexibility in selecting appropriate resource servers for workflow tasks. The time-aware strategy schedules the pre-scheduled workflow tasks at suitable idle times, considering the current workflow task scheduling situation. Experimental results demonstrate that the proposed algorithm can satisfies the delivery time constraints for cloud users and achieves a significant reduction in the execution cost of workflows.