Deadline-Constrained and Cost-Effective Multi-Workflow Scheduling with Uncertainty in Cloud Control Systems

In cloud control systems, generating an efficient and economical workflow scheduling strategy for deadline-constrained workflow applications, especially in uncertain multi-workflow dynamic scheduling processes, is a crucial challenge. To optimize the total cost of workflow scheduling, the authors propose a cost-driven heuristic scheduling algorithm F-MWSA which consists of two phases: Fuzzy deadline distribution and fuzzy task scheduling. In the fuzzy deadline distribution phase, a new workflow deadline distribution strategy with fuzziness is designed to obtain the sub-deadline constraint of each task. The fuzzy task scheduling phase focuses on a cost-effective strategy to assign tasks to cloud resources, reducing multi-workflow scheduling costs. Performance evaluations on five real-world workflows demonstrate that the proposed F-MWSA outperforms the baseline policy in terms of total cost, success ratio, resource utilization, and makespan.