@inproceedings{47fb86a5c380441589d1c7f2b5a34e6c,
title = "Automated and Reproducible Application Traces Generation for IoT Applications",
abstract = "In this paper, we investigate and present how to generate application traces of IoT (Internet of Things) Applications in an automated, repeatable and reproducible manner. By using the FIT IoT-Lab large scale testbed and relying on state-of-the-art software engineering techniques, we are able to produce, collect and share artifacts and datasets in an automated way. This makes it easy to track the impact of software updates or changes in the radio environment both on a small scale, e.g. during a single day, and on a large scale, e.g. during several weeks. By providing both the source code for the trace generation as well as the resulting datasets, we hope to reduce the learning curve to develop such applications and encourage re-usability as well as pave the way for the replication of our results. While we focus in this work on IoT networks, we believe such an approach could be of used in many other networking domains.",
keywords = "802.15.4, automation, datasets, experiments, network, reproducibility, testbed, traces",
author = "Nina Santi and R{\'e}my Gr{\"u}nblatt and Brandon Foubert and Aroosa Hameed and John Violos and Aris Leivadeas and Nathalie Mitton",
note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 17th ACM Symposium on QoS and Security for Wireless and Mobile Networks, Q2SWinet 2021 ; Conference date: 22-11-2021 Through 26-11-2021",
year = "2021",
month = nov,
day = "22",
doi = "10.1145/3479242.3487321",
language = "English",
series = "Q2SWinet 2021 - Proceedings of the 17th ACM Symposium on QoS and Security for Wireless and Mobile Networks",
publisher = "Association for Computing Machinery, Inc",
pages = "17--24",
booktitle = "Q2SWinet 2021 - Proceedings of the 17th ACM Symposium on QoS and Security for Wireless and Mobile Networks",
}