A Failure Prediction Platform for Internet of Things Applications

Daniel Gaudio, Amil Imeri, Pascal Hirmer

2022

Abstract

In the Internet of Things (IoT), interconnected devices communicate through standard Internet protocols to reach common goals. The IoT has reached a wide range of different domains including home automation, health, or manufacturing. With the rising amount of IoT applications, the demand for robustness is increasing as well, which is a difficult issue especially in large IoT applications including hundreds or even thousands of different devices. Devices tend to be very volatile and prone to failures. Usually, IoT devices are comprised of cheap hardware components which enables the creation of larger applications but also leads to an increased amount of failures that endanger operation of the IoT applications. To help in increasing robustness in the IoT, in this paper, we introduce the Failure Prediction Prediction Platform (FPP) for Internet of Things applications, which uses a machine learning based approach to predict failures. We evaluate our platform by showing how different failure prediction algorithms can be integrated and applied.

Paper Citation

in Harvard Style

Gaudio D., Imeri A. and Hirmer P. (2022). A Failure Prediction Platform for Internet of Things Applications. In Proceedings of the 7th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, ISBN 978-989-758-564-7, pages 141-148. DOI: 10.5220/0011033700003194

in Bibtex Style

@conference{iotbds22,
author={Daniel Gaudio and Amil Imeri and Pascal Hirmer},
title={A Failure Prediction Platform for Internet of Things Applications},
booktitle={Proceedings of the 7th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,},
year={2022},
pages={141-148},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011033700003194},
isbn={978-989-758-564-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 7th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,
TI - A Failure Prediction Platform for Internet of Things Applications
SN - 978-989-758-564-7
AU - Gaudio D.
AU - Imeri A.
AU - Hirmer P.
PY - 2022
SP - 141
EP - 148
DO - 10.5220/0011033700003194