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Emergency Message Reduction Scheme Using Markov Prediction Model in VANET Environment

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Quality, Reliability, Security and Robustness in Heterogeneous Networks (QShine 2016)


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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This research was partly funded by the National Science Council of the R.O.C. under grants MOST 104-2221-E-197- 014 -.

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Correspondence to Han-Chieh Chao .

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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Cho, HH., Huang, WC., Shih, T.K., Chao, HC. (2017). Emergency Message Reduction Scheme Using Markov Prediction Model in VANET Environment. In: Lee, JH., Pack, S. (eds) Quality, Reliability, Security and Robustness in Heterogeneous Networks. QShine 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 199. Springer, Cham.

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  • Print ISBN: 978-3-319-60716-0

  • Online ISBN: 978-3-319-60717-7

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