Simulate Congestion Prediction in a Wireless Network Using the LSTM Deep Learning Model

Achieved wireless networks since its beginning the prevalent wide due to the increasing wireless devices represented by smart phones and laptop, and the proliferation of networks coincides with the high speed and ease of use of the Internet and enjoy the delivery of various data such as video clips...

Full description

Bibliographic Details
Main Author: Nada Badr Jarah
Format: Article
Language:fas
Published: University of Tehran 2019-12-01
Series:Journal of Information Technology Management
Subjects:
Online Access:https://jitm.ut.ac.ir/article_74762_442b6197cd4283c5f42ba88fadcacd64.pdf
_version_ 1818054990913077248
author Nada Badr Jarah
author_facet Nada Badr Jarah
author_sort Nada Badr Jarah
collection DOAJ
description Achieved wireless networks since its beginning the prevalent wide due to the increasing wireless devices represented by smart phones and laptop, and the proliferation of networks coincides with the high speed and ease of use of the Internet and enjoy the delivery of various data such as video clips and games. Here's the show the congestion problem arises and represent   aim of the research is to avoid congestion at APs to wireless networks by adding a control before congestion occurs. A wireless connection was made using the Android system, and congestion was predicted based on the analysis of wireless communication packages around the access point using the LSTM deep learning model. The results show that if the amount of information in the input data is large, a more accurate prediction can be made.
first_indexed 2024-12-10T12:05:50Z
format Article
id doaj.art-7ff3f24d4fde40fba3a5f59d8c123a6a
institution Directory Open Access Journal
issn 2008-5893
2423-5059
language fas
last_indexed 2024-12-10T12:05:50Z
publishDate 2019-12-01
publisher University of Tehran
record_format Article
series Journal of Information Technology Management
spelling doaj.art-7ff3f24d4fde40fba3a5f59d8c123a6a2022-12-22T01:49:28ZfasUniversity of TehranJournal of Information Technology Management2008-58932423-50592019-12-01114707910.22059/jitm.2019.7476274762Simulate Congestion Prediction in a Wireless Network Using the LSTM Deep Learning ModelNada Badr Jarah0Assistant Professor, Statistics Department, Collage of management and economic, University of Basra, Iraq.Achieved wireless networks since its beginning the prevalent wide due to the increasing wireless devices represented by smart phones and laptop, and the proliferation of networks coincides with the high speed and ease of use of the Internet and enjoy the delivery of various data such as video clips and games. Here's the show the congestion problem arises and represent   aim of the research is to avoid congestion at APs to wireless networks by adding a control before congestion occurs. A wireless connection was made using the Android system, and congestion was predicted based on the analysis of wireless communication packages around the access point using the LSTM deep learning model. The results show that if the amount of information in the input data is large, a more accurate prediction can be made.https://jitm.ut.ac.ir/article_74762_442b6197cd4283c5f42ba88fadcacd64.pdfapandroidcongestiondeep learninglstmwireless networks
spellingShingle Nada Badr Jarah
Simulate Congestion Prediction in a Wireless Network Using the LSTM Deep Learning Model
Journal of Information Technology Management
ap
android
congestion
deep learning
lstm
wireless networks
title Simulate Congestion Prediction in a Wireless Network Using the LSTM Deep Learning Model
title_full Simulate Congestion Prediction in a Wireless Network Using the LSTM Deep Learning Model
title_fullStr Simulate Congestion Prediction in a Wireless Network Using the LSTM Deep Learning Model
title_full_unstemmed Simulate Congestion Prediction in a Wireless Network Using the LSTM Deep Learning Model
title_short Simulate Congestion Prediction in a Wireless Network Using the LSTM Deep Learning Model
title_sort simulate congestion prediction in a wireless network using the lstm deep learning model
topic ap
android
congestion
deep learning
lstm
wireless networks
url https://jitm.ut.ac.ir/article_74762_442b6197cd4283c5f42ba88fadcacd64.pdf
work_keys_str_mv AT nadabadrjarah simulatecongestionpredictioninawirelessnetworkusingthelstmdeeplearningmodel