Resource Usage of Applications Running on Raspberry Pi Devices

The collection and construction of this dataset were organized by the Queen's Telecommunications Research Lab (TRL) and led by Ruslan Kain, a Ph.D. student at TRL. The dataset includes dynamic resource usage information associated with running edge-native applications on a set of four heterogeneous Raspberry Pi 4 Devices. The four Raspberry Pi 4 devices have 2, 4, and 8 GB RAM sizes, and CPU frequencies of 1200, 1500, and 1800 MHz. This is to establish heterogeneity of the devices used and collected data and to enable data-based applications for Edge Computing Research. The resource usage measurements have a five-second granularity. We managed to collect more than 550 thousand unique data points representing the 768 hours of running applications on Raspberry Pi Devices. Our dataset is publicly available on the Borealis platform in an effort to help other researchers in the field conduct edge computing resource usage analysis. The dataset size is around 444 MB, consisting of 74 comma-separated values (CSV) files. Check the README file for the full details on the structure and content of the dataset.