@inproceedings{292b581d4f574933829f99148bbe71a6,
title = "AGV Quality of Service Throughput Prediction via Neural Networks",
abstract = "The recent development of Autonomous Guided Vehicles (AGV) use in industry has resulted in the need to model new solutions based on the latest technological achievements. One of the areas worth attention and development is Quality of Service (QoS) in relation to communication between vehicles. QoS makes it possible to divide the bandwidth in such a way that tasks performed by devices are completed with a certain priority. However, in order to manage these resources effectively, it is necessary to anticipate available network throughput. Therefore, this paper presents a neural-based model to ensure throughput prediction for AGV. The proposed solution assumes the use of information on both historical throughput values and data obtained from other sensors that AGV are equipped with. Therefore, the idea is to integrate two neural networks with another network, which is supposed to predict the result based on these two previously obtained predictions. Ultimately, prediction results with a Root Mean Squared Error (RMSE) of 0.1 for the downlink and 1.6 for the uplink were obtained.",
keywords = "AGV, QoS, deep learning, predictive models, throughput prediction",
author = "Katarzyna Prokop and Dawid Polap and Gautam Srivastava",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Big Data, BigData 2023 ; Conference date: 15-12-2023 Through 18-12-2023",
year = "2023",
doi = "10.1109/BigData59044.2023.10386241",
language = "English",
series = "Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2493--2498",
editor = "Jingrui He and Themis Palpanas and Xiaohua Hu and Alfredo Cuzzocrea and Dejing Dou and Dominik Slezak and Wei Wang and Aleksandra Gruca and Lin, \{Jerry Chun-Wei\} and Rakesh Agrawal",
booktitle = "Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023",
address = "United States",
}