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...
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doaj-7ff3f24d4fde40fba3a5f59d8c123a6a2020-11-25T02:43:22ZfasUniversity of TehranJournal of Information Technology Management 2008-58932423-50592019-12-01114707910.22059/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 |
collection |
DOAJ |
language |
fas |
format |
Article |
sources |
DOAJ |
author |
Nada Badr Jarah |
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 |
author_facet |
Nada Badr Jarah |
author_sort |
Nada Badr Jarah |
title |
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_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_sort |
simulate congestion prediction in a wireless network using the lstm deep learning model |
publisher |
University of Tehran |
series |
Journal of Information Technology Management |
issn |
2008-5893 2423-5059 |
publishDate |
2019-12-01 |
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. |
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 |
_version_ |
1724769660810821632 |