Emergency message reduction scheme using markov prediction model in VANET environment

Hsin Hung Cho; Wei Chih Huang; Timothy K. Shih; Han Chieh Chao

doi:10.1007/978-3-319-60717-7_13

Emergency message reduction scheme using markov prediction model in VANET environment

Hsin Hung Cho, Wei Chih Huang, Timothy K. Shih, Han Chieh Chao

Department of Computer Science and Information Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Today’s vehicles technologies are getting better as well as the price of the vehicle is not too expensive so that almost every household has an own car. However, road space is limited so there is high opportunity to see the accidents on the high dense road. Current VANET technology has been able to inform rear vehicles do not go there so that the traffic congestion can be reduced. In this scenario, there are very large amount of emergency message will be generated. It will increase the burden of road side unit. In this paper, we propose a Markov-based model to predict behavior of vehicles so that we can identify which cars really need to receive this message. Simulation results show that this method can reduces the unnecessary message transmission indeed.

Original language	English
Title of host publication	Quality, Reliability, Security and Robustness in Heterogeneous Networks - 12th International Conference, QShine 2016, Proceedings
Editors	Sangheon Pack, Jong-Hyouk Lee
Publisher	Springer Verlag
Pages	129-137
Number of pages	9
ISBN (Print)	9783319607160
DOIs	https://doi.org/10.1007/978-3-319-60717-7_13
State	Published - 2017
Event	12th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2016 - Seoul, Korea, Republic of Duration: 7 Jul 2016 → 8 Jul 2016

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume	199
ISSN (Print)	1867-8211

Conference

Conference	12th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2016
Country/Territory	Korea, Republic of
City	Seoul
Period	7/07/16 → 8/07/16

Keywords

Emergency service
Markov chain
Prediction model
VANET

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-319-60717-7_13

Cite this

Cho, H. H., Huang, W. C., Shih, T. K., & Chao, H. C. (2017). Emergency message reduction scheme using markov prediction model in VANET environment. In S. Pack, & J.-H. Lee (Eds.), Quality, Reliability, Security and Robustness in Heterogeneous Networks - 12th International Conference, QShine 2016, Proceedings (pp. 129-137). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 199). Springer Verlag. https://doi.org/10.1007/978-3-319-60717-7_13

Cho, Hsin Hung ; Huang, Wei Chih ; Shih, Timothy K. et al. / Emergency message reduction scheme using markov prediction model in VANET environment. Quality, Reliability, Security and Robustness in Heterogeneous Networks - 12th International Conference, QShine 2016, Proceedings. editor / Sangheon Pack ; Jong-Hyouk Lee. Springer Verlag, 2017. pp. 129-137 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST).

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abstract = "Today{\textquoteright}s vehicles technologies are getting better as well as the price of the vehicle is not too expensive so that almost every household has an own car. However, road space is limited so there is high opportunity to see the accidents on the high dense road. Current VANET technology has been able to inform rear vehicles do not go there so that the traffic congestion can be reduced. In this scenario, there are very large amount of emergency message will be generated. It will increase the burden of road side unit. In this paper, we propose a Markov-based model to predict behavior of vehicles so that we can identify which cars really need to receive this message. Simulation results show that this method can reduces the unnecessary message transmission indeed.",

keywords = "Emergency service, Markov chain, Prediction model, VANET",

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Cho, HH, Huang, WC, Shih, TK & Chao, HC 2017, Emergency message reduction scheme using markov prediction model in VANET environment. in S Pack & J-H Lee (eds), Quality, Reliability, Security and Robustness in Heterogeneous Networks - 12th International Conference, QShine 2016, Proceedings. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 199, Springer Verlag, pp. 129-137, 12th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2016, Seoul, Korea, Republic of, 7/07/16. https://doi.org/10.1007/978-3-319-60717-7_13

Emergency message reduction scheme using markov prediction model in VANET environment. / Cho, Hsin Hung; Huang, Wei Chih; Shih, Timothy K. et al.
Quality, Reliability, Security and Robustness in Heterogeneous Networks - 12th International Conference, QShine 2016, Proceedings. ed. / Sangheon Pack; Jong-Hyouk Lee. Springer Verlag, 2017. p. 129-137 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 199).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Emergency message reduction scheme using markov prediction model in VANET environment

AU - Cho, Hsin Hung

AU - Huang, Wei Chih

AU - Shih, Timothy K.

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AB - Today’s vehicles technologies are getting better as well as the price of the vehicle is not too expensive so that almost every household has an own car. However, road space is limited so there is high opportunity to see the accidents on the high dense road. Current VANET technology has been able to inform rear vehicles do not go there so that the traffic congestion can be reduced. In this scenario, there are very large amount of emergency message will be generated. It will increase the burden of road side unit. In this paper, we propose a Markov-based model to predict behavior of vehicles so that we can identify which cars really need to receive this message. Simulation results show that this method can reduces the unnecessary message transmission indeed.

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ER -

Cho HH, Huang WC, Shih TK, Chao HC. Emergency message reduction scheme using markov prediction model in VANET environment. In Pack S, Lee JH, editors, Quality, Reliability, Security and Robustness in Heterogeneous Networks - 12th International Conference, QShine 2016, Proceedings. Springer Verlag. 2017. p. 129-137. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST). doi: 10.1007/978-3-319-60717-7_13

Emergency message reduction scheme using markov prediction model in VANET environment

Abstract

Publication series

Conference

Keywords

UN SDGs

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