Workflows are prevalent in today’s computing infrastructures as they support many domains. Different Quality of Service (QoS) requirements of both users and providers makes workflow scheduling challenging. Meeting the challenge requires an overview of state-of-art in workflow scheduling. Sifting through literature to find the state-of-art can be daunting, for both newcomers and experienced researchers. Surveys are an excellent way to address questions regarding the different techniques, policies, emerging areas, and opportunities present, yet they rarely take a systematic approach and publish their tools and data on which they are based. Moreover, the communities behind these articles are rarely studied. We attempt to address these shortcomings in this work.

We introduce and open-source an instrument used to combine and store article meta-data. Using this meta-data, we characterize and taxonomize the workflow scheduling community and four areas within workflow scheduling: (1) the workflow formalism, (2) workflow allocation, (3) resource provisioning, and (4) applications and services. In each characterization, we obtain important keywords overall and per year, identify keywords growing in importance, get insight into the structure and relations within each community, and perform a systematic literature survey per part to validate and complement our taxonomies

工作流在当今的计算基础架构中很普遍，因为它们支持许多域。用户和提供商的服务质量（QoS）要求不同，这使工作流调度具有挑战性。迎接挑战需要对工作流程调度方面的最新技术进行概述。对于新来者和经验丰富的研究人员而言，筛选文献以寻找最新技术可能是艰巨的。调查是解决有关不同技术，政策，新兴领域和当前机会的问题的一种极好的方法，但是它们很少采用系统的方法并发布其所基于的工具和数据。而且，社区这些文章后面很少进行研究。我们试图解决这项工作中的这些缺点。

我们引入并开源了一种用于合并和存储文章元数据的工具。使用此元数据，我们可以对工作流调度社区和工作流调度中的四个区域进行表征和分类：（1）工作流形式化，（2）工作流分配，（3）资源供应以及（4）应用程序和服务。在每个表征中，我们总体上和每年都获得重要的关键字，识别重要性不断提高的关键字，深入了解每个社区内的结构和关系，并对每个部分进行系统的文献调查以验证和补充我们的分类法