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Workflows are prevalent in today's computing infrastructures. The workflowmodel support various different domains, from machine learning to finance andfrom astronomy to chemistry. Different Quality-of-Service (QoS) requirementsand other desires of both users and providers makes workflow scheduling a toughproblem, especially since resource providers need to be as efficient aspossible with their resources to be competitive. To a newcomer or even anexperienced researcher, sifting through the vast amount of articles can be adaunting task. Questions regarding the difference techniques, policies,emerging areas, and opportunities arise. Surveys are an excellent way to coverthese questions, yet surveys rarely publish their tools and data on which it isbased. Moreover, the communities that are behind these articles are rarelystudied. We attempt to address these shortcomings in this work. We focus onfour areas within workflow scheduling: 1) the workflow formalism, 2) workflowallocation, 3) resource provisioning, and 4) applications and services. Eachpart features one or more taxonomies, a view of the community, important andemerging keywords, and directions for future work. We introduce and makeopen-source an instrument we used to combine and store article meta-data. Usingthis meta-data, we 1) obtain important keywords overall and per year, percommunity, 2) identify keywords growing in importance, 3) get insight into thestructure and relations within each community, and 4) perform a systematicliterature survey per part to validate and complement our taxonomies.

A Survey and Annotated Bibliography of Workflow Scheduling in Computing  Infrastructures: Community, Keyword, and Article Reviews -- Extended  Technical Report