Fault-tolerant elastic scheduling algorithm for workflow in Cloud systems

With the increasing functionality and complexity of Cloud systems, fault tolerance becomes an essential requirement for tasks executed in Cloud systems, especially for the workflow with dependent relationship among tasks. The existing fault-tolerant scheduling algorithms cannot be used for workflow in Cloud systems directly, which have two key features: virtualization and elasticity. In this paper, we propose an offline fault-tolerant elastic scheduling algorithm for workflow in Cloud systems (FTESW). After analyzing the constrains of primary-backup scheduling in Cloud systems caused by the dependence among tasks in the submitted workflow, an elastic mechanism in the context of fault tolerance is designed to dynamically adjust the resource provisioning based on the resource request by adopting the technology of resource migration. Then, the FTESW is proposed to achieve both fault tolerance and high resource utilization for workflow in Cloud systems. To verify the effectiveness of the proposed FTESW, a series of simulation experiments are conducted on both randomly generated workflows and real-world workflows. The simulation results demonstrate that the proposed FTESW is able to effectively provide a corresponding fault-tolerant scheduling strategy for workflow with high resource utilization in Cloud systems and has better performance than the corresponding competitors.