Researchers building multi-agent algorithms typically work with abstracted away from real applications. The abstracted problem instances allow systematic and detailed investigations of new algorithms. However, a key question is how to apply algoeveloped on an abstract problem, in a real application. In this paper, we report on what was required to apply a particular ted resource allocation algorithm developed for an abstract coordination problem in a real hardware application. A probabilistic representation of resources and tasks was used to deal with uncertainty and dynamics and local reasoning was used to deal with delays in the distributed resource allocation algorithm. The probabilistic representation and local reasoning enabled the use of the multi-agent algorithm which, in turn, improved the overall performance of the system.