Internet of Things orchestration using DagOn∗ workflow engine

The increasing of connected tiny, low-power, embedded devices, grouped into the generic definition of "Internet of Things" (IoT), raised remarkably the amount of in-situ collected data. However, at the time of writing, IoT devices have limited storage and computation resources if compared with a cloud computing or on-premises infrastructure. IoT devices often suffer for reduced connectivity due to the place of the deployment or other technical, environmental or economic reasons. In this work, we present the DagOn∗ workflow engine as a part of an IoT orchestration scenario oriented to operational environmental prediction. Our novel approach is devoted to join the two worlds of workflows, in which each task runs on a dynamically allocated computational infrastructure, with tiny jobs targeted to embedded devices hosting sensors and actuators. We show our preliminary results applied to a demonstration use case. We are confident that further development of the proposed technology will affect positively production applications for massive and geographically distributed data collection.