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Next Generation Information Processing System pp 12–22Cite as

On-Demand Joint Predictive Flooding in Vehicular Ad Hoc Networks

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1162 ))

Abstract

Vehicular ad hoc networks (VANET) are flavor of mobile ad hoc networks. With the increase in the development of mobile technology in the last decade or so, we see increased interest in the development in VANET protocols as well. In this paper, we propose a routing protocol that uses predictive position information of neighboring nodes for data dissemination. The highly dynamic topology of VANET results in route discovered by a routing protocol to be intermittent. Hence, in this work we propose a predictive flooding in VANET (PFV) which has a flavor of flooding protocol for data transfer. Our results show that the PFV considerably reduces the network load in terms of forwards with an increase in the performance of data dissemination as well.

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Author information

Authors and Affiliations

  1. Department of SCSE, VIT University, Chennai, India

    H. N. Jithendra & D. Rekha

Authors
  1. H. N. Jithendra
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  2. D. Rekha
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Corresponding author

Correspondence to H. N. Jithendra .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Dr. Babasaheb Ambedkar Technological University, Lonere, Maharashtra, India

    Prachi Deshpande

  2. Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  3. Department of Electronics and Telecommunication Engineering, Dr. Babasaheb Ambedkar Technological University, Lonere, Maharashtra, India

    Brijesh Iyer

  4. School of Information Science and Engineering, University of Jinan, Jinan, Shandong, China

    Kun Ma

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Jithendra, H.N., Rekha, D. (2021). On-Demand Joint Predictive Flooding in Vehicular Ad Hoc Networks. In: Deshpande, P., Abraham, A., Iyer, B., Ma, K. (eds) Next Generation Information Processing System. Advances in Intelligent Systems and Computing, vol 1162 . Springer, Singapore. https://doi.org/10.1007/978-981-15-4851-2_2

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