With the increase in internet of things (IoT) applications' range and scale, it is essential to test the applications before deploying them in the real world. Most common approaches utilize simulations and testbeds; however, these methods lack real-time failure scenarios and the capability to scale, respectively. A virtual environment is a suitable approach that overcomes these drawbacks further, IoT applications using cloud computing have evolved to shift some computing and storage capabilities to the edge networks for ensuring adherence to strict latency constraints for real-time applications. This led to the emergence of fog computing which provides lower latency and better security, among other advantages. As for any processing tasks, scheduling becomes a critical concern for matching the tasks with the devices having appropriate resources. This paper analyzes a hybridized fog scheduling algorithm based on a ranking approach considering latency as the main parameter. It builds a software layer for scheduling on top of the validating internet of things at large scales (VIoLET) infrastructure. The results are compared with the round-robin scheduling algorithm, and it is found that the hybridized algorithm provides closer actual latency values to the expected.