Low-time complexity budget-deadline constrained workflow scheduling on heterogeneous resources
In utility computing models, users consume services based on their Quality of Service (QoS) requirements. QoS provides a basis for task scheduling, but it also makes task scheduling problems more complex. In this paper, we present a heuristic scheduling algorithm, named Budget-Deadline Constrained Workflow Scheduling (BDCWS). The algorithm calculates the task priority by a new method to balance the two QoS factors of time and cost, thereby effectively improving the success rate of applications without increasing the algorithm time complexity. Experiments regarding aspects of randomly generated graphs and real-world application graphs are performed, and the results reveal that the BDCWS outperforms the existing algorithms on the both aspects.