Workflow scheduling in cloud computing environments is nowadays a hot topic as scientific workflows application are gradually taking advantage of commercial cloud assets. Common users’ quality of service (QoS) requirements are the respect of defined budget and deadline when executing their workflow job. Since execution cost minimization and completion time minimization are contradictory objectives, addressing such issue through trade-off function approaches have proved to be an efficient way. This paper presents the Cost-Time Trade-off efficient Workflow Scheduling with Dynamic provisioning (CTTWSDP) algorithm. CTTWSDP relies on dynamic VMs provisioning with a limited number of leased VMs, and a cost-time trade-off function over heterogeneous instances to determine the most viable schedule. CTTWSDP also proposed an improved Implicit Requested Instance Types Range (IRITR) evaluation, which is a scheduling concept introduced in our previous work. The IRITR evaluation aims at determining a range of VMs instance types that best suits the workflow execution, in order to avoid overbidding and underbidding that may lead to budget and deadline violation respectively. The results of simulations prove the effectiveness of the proposal. CTTWSDP achieves a 17.09–76.06% higher success rate when compared to four state-of-the-art algorithms. Furthermore, ANOVA along with Tukey–Kramer post-hoc tests have been conducted, revealing the effectiveness of CTTWSDP over three of the baseline algorithm, while for the fourth one the outperformance of CTTWSDP is not statistically significant. An analysis of the standard deviation of the success rate proves that CTTWSDP is more stable in its performance no matter the type and the workload of the workflow. With a standard deviation of 6.73, smaller than the ones obtained by the other algorithms from 18.66 to 34.10.

随着科学工作流应用逐渐利用商业云资产，云计算环境中的工作流调度成为当今的热门话题。普通用户的服务质量（QoS）要求是在执行其工作流程作业时要考虑已定义的预算和截止日期。由于最小化执行成本和最小化完成时间是矛盾的目标，因此通过折衷函数方法解决此类问题已被证明是一种有效的方法。本文提出了一种具有动态配置的成本－时间折衷的高效工作流调度（CTTWSDP）算法。CTTWSDP依赖于动态VM的配置和有限数量的租用VM，以及在异构实例上进行成本-时间权衡的功能，以确定最可行的计划。CTTWSDP还提出了改进的隐式请求实例类型范围（IRITR）评估，这是我们先前工作中引入的调度概念。IRITR评估旨在确定最适合工作流执行的一系列VM实例类型，以避免避免可能导致预算和截止期限违反的过高和过低的出价。仿真结果证明了该方案的有效性。与四种最新算法相比，CTTWSDP的成功率提高了17.09–76.06％。此外，还进行了方差分析和Tukey–Kramer事后测试，揭示了CTTWSDP在三种基准算法上的有效性，而对于第四种算法，CTTWSDP的性能不具有统计学意义。对成功率标准偏差的分析表明，无论工作流程的类型和工作量如何，CTTWSDP的性能都更加稳定。标准偏差为6.73，小于其他算法从18.66到34.10所获得的标准偏差。