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Mobility prediction method for vehicular network using Markov chain

This paper proposes mobility prediction technique via Markov Chains with an input of user’s mobile data traces to predict the user’s movement in wireless network. The main advantage of this method is prediction will give knowledge of user’s movement in advance even in fast moving vehicle. Furthermor...

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Main Authors: Hasbollah, Arfah, Syed Ariffin, Sharifah Hafizah, Fisal, Norsheila
Format: Article
Language:English
Published: Penerbit UTM Press 2016
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/71210/1/ArfahHasbollah2016_Mobilitypredictionmethodforvehicular.pdf
http://eprints.utm.my/id/eprint/71210/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84973397914&doi=10.11113%2fjt.v78.8885&partnerID=40&md5=86f0fcc9e8d0b447fd4a6adb29a473b8
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spelling my.utm.712102017-11-15T04:06:35Z http://eprints.utm.my/id/eprint/71210/ Mobility prediction method for vehicular network using Markov chain Hasbollah, Arfah Syed Ariffin, Sharifah Hafizah Fisal, Norsheila TK Electrical engineering. Electronics Nuclear engineering This paper proposes mobility prediction technique via Markov Chains with an input of user’s mobile data traces to predict the user’s movement in wireless network. The main advantage of this method is prediction will give knowledge of user’s movement in advance even in fast moving vehicle. Furthermore, the information from prediction result will be use to assist handover procedure by reserve resource allocation in advance in vehicular network. This algorithm is simple and can be computed within short time, thus the implementation of this technique will give the significant impact especially on higher speed vehicle. Finally, an experiment is performed using real mobile user data traces as input for Markov chain to predict next user movement. To evaluate the effectiveness of the proposed method, MATLAB simulations are carried out with several users under same location zone. The results show that the proposed method predicts have good performance which is 30 of mobile users achieved 100 of prediction accuracy. Penerbit UTM Press 2016 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/71210/1/ArfahHasbollah2016_Mobilitypredictionmethodforvehicular.pdf Hasbollah, Arfah and Syed Ariffin, Sharifah Hafizah and Fisal, Norsheila (2016) Mobility prediction method for vehicular network using Markov chain. Jurnal Teknologi, 78 (6-2). pp. 7-13. ISSN 0127-9696 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84973397914&doi=10.11113%2fjt.v78.8885&partnerID=40&md5=86f0fcc9e8d0b447fd4a6adb29a473b8
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Hasbollah, Arfah
Syed Ariffin, Sharifah Hafizah
Fisal, Norsheila
Mobility prediction method for vehicular network using Markov chain
description This paper proposes mobility prediction technique via Markov Chains with an input of user’s mobile data traces to predict the user’s movement in wireless network. The main advantage of this method is prediction will give knowledge of user’s movement in advance even in fast moving vehicle. Furthermore, the information from prediction result will be use to assist handover procedure by reserve resource allocation in advance in vehicular network. This algorithm is simple and can be computed within short time, thus the implementation of this technique will give the significant impact especially on higher speed vehicle. Finally, an experiment is performed using real mobile user data traces as input for Markov chain to predict next user movement. To evaluate the effectiveness of the proposed method, MATLAB simulations are carried out with several users under same location zone. The results show that the proposed method predicts have good performance which is 30 of mobile users achieved 100 of prediction accuracy.
format Article
author Hasbollah, Arfah
Syed Ariffin, Sharifah Hafizah
Fisal, Norsheila
author_facet Hasbollah, Arfah
Syed Ariffin, Sharifah Hafizah
Fisal, Norsheila
author_sort Hasbollah, Arfah
title Mobility prediction method for vehicular network using Markov chain
title_short Mobility prediction method for vehicular network using Markov chain
title_full Mobility prediction method for vehicular network using Markov chain
title_fullStr Mobility prediction method for vehicular network using Markov chain
title_full_unstemmed Mobility prediction method for vehicular network using Markov chain
title_sort mobility prediction method for vehicular network using markov chain
publisher Penerbit UTM Press
publishDate 2016
url http://eprints.utm.my/id/eprint/71210/1/ArfahHasbollah2016_Mobilitypredictionmethodforvehicular.pdf
http://eprints.utm.my/id/eprint/71210/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84973397914&doi=10.11113%2fjt.v78.8885&partnerID=40&md5=86f0fcc9e8d0b447fd4a6adb29a473b8
_version_ 1643656136660877312
score 13.211869

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