Using component ensembles for modeling autonomic component collaboration in smart farming

Abstract

Smart systems have become key solutions for many application areas including autonomous farming. The trend we can see now in the smart systems is that they shift from single isolated autonomic and self-adaptive components to larger ecosystems of heavily cooperating components. This increases the reliability and often the cost-effectiveness of the system by replacing one big costly device with a number of smaller and cheaper ones. In this paper, we demonstrate the effect of synergistic collaboration among autonomic components in the domain of smart farming---in particular, the use-case we employ in the demonstration stems from the AFar-Cloud EU project. We exploit the concept of autonomic component ensembles to describe situation-dependent collaboration groups (so called ensembles). The paper shows how the autonomic component ensembles can easily capture complex collaboration rules and how they can include both controllable autonomic components (i.e. drones) and non-controllable environment agents (flocks of birds in our case). As part of the demonstration, we provide an open-source implementation that covers both the specification of the autonomic components and ensembles of the use case, and the discrete event simulation and real-time visualization of the use case. We believe this is useful not only to demonstrate the effectiveness of architectures of collaborative autonomic components for dealing with real-life tasks, but also to build further experiments in the domain.