Cloud computing has become a promising solution for scientific workflow applications, due to its various assets. Workflow scheduling is a well-known NP-complete problem, so difficult to solve since there are no optimal solutions. Several workflow scheduling works aim at optimizing the makespan and the budget. However, more investigations are needed for appropriate resources chosing in the large set of instance types offered in cloud environments. This paper proposes a new scheduling algorithm called Cost-Time Trade-off efficient Workflow Scheduling (CTTWS), which consists of four main steps: task selection, Implicit Requested Instance Types Range (IRITR) evaluation, spare budget evaluation and VM selection. The IRITR evaluation is a novel scheduling concept, which 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. Compared to previous work, the results of simulations prove the effectiveness of our approach, especially when there is a large variety of instance types. This confirm that paying attention to the type of resources and their number is vital.

由于其各种资产，云计算已成为科学工作流程应用程序的有前途的解决方案。工作流调度是一个众所周知的NP完全问题，由于没有最佳解决方案，因此难以解决。几个工作流计划工作旨在优化工期和预算。但是，对于在云环境中提供的大量实例类型中选择合适的资源，还需要进行更多调查。本文提出了一种新的调度算法，称为成本时间权衡有效工作流调度（CTTWS），它包括四个主要步骤：任务选择，隐式请求实例类型范围（IRITR）评估，备用预算评估和VM选择。IRITR评估是一种新颖的计划概念，这样做的目的是确定最适合工作流程执行的一系列VM实例类型，以避免过度出价和出价不足，分别导致预算和截止日期的违反。与以前的工作相比，仿真的结果证明了我们方法的有效性，特别是当实例类型繁多时。这证实了关注资源的类型和数量至关重要。