Workflow underlies most process automation software, such as those for product lines, business processes, and scientific computing. However, current Cloud Computing based workflow systems cannot support real-time applications due to network latency, which limits their application in many IoT systems such as smart healthcare and smart traffic. Fog Computing extends the Cloud by providing virtualized computing resources close to the End Devices so that the response time of accessing computing resources can be reduced significantly. However, how to most effectively manage heterogeneous resources and different computing tasks in the Fog is a big challenge. In this paper, we introduce "FogWorkflowSim" an efficient and extensible toolkit for automatically evaluating resource and task management strategies in Fog Computing with simulated user-defined workflow applications. Specifically, FogWorkflowSim is able to: 1) automatically set up a simulated Fog Computing environment for workflow applications; 2) automatically execute user submitted workflow applications; 3) automatically evaluate and compare the performance of different computation offloading and task scheduling strategies with three basic performance metrics, including time, energy and cost. FogWorkflowSim can serve as an effective experimental platform for researchers in Fog based workflow systems as well as practitioners interested in adopting Fog Computing and workflow systems for their new software projects. (Demo video: https://youtu.be/AsMovcuSkx8).

@inproceedings{paperbot5223,
  title = {FogWorkflowSim: An Automated Simulation Toolkit for Workflow Performance Evaluation in Fog Computing},
  author = {Xiao Liu and Lingmin Fan and Jia Xu and Xuejun Li and Lina Gong and John Grundy and Yun Yang},
  booktitle = {ASE},
  year = {2019},
  doi = {10.1109/ase.2019.00115}
}