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The Model of WBAN Data Acquisition Network Based on UFP

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Distributed Computer and Communication Networks (DCCN 2020)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 12563))

Abstract

The paper determines the general model of an unmanned flying platforms based network for collecting information from wearable wireless body area networks. There are considered several possible approaches to its implementation. A list of tasks to be solved and their features in the framework of building a network are given. There are proposed variants of optimal network radio technologies and topologies, antenna devices and types of unmanned flying platforms to create the acquisition network. Variants of implementation of the interaction protocol and methods of organizing secure data transmission, taking into account the peculiarities of the problem being solved, are recommended.

Supported by RFBR according to the research project No.20-37-70059.

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Author information

Authors and Affiliations

  1. St.Petersburg State University of Telecommunications, 22 Bolshevikov Pr., St.Petersburg, 193232, Russian Federation

    S. Vladimirov & R. Kirichek

  2. V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, 65 Profsoyuznaya Street, Moscow, 117997, Russian Federation

    V. Vishnevsky & A. Larionov

Authors
  1. S. Vladimirov
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  2. V. Vishnevsky
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  3. A. Larionov
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  4. R. Kirichek
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Corresponding author

Correspondence to S. Vladimirov .

Editor information

Editors and Affiliations

  1. Institute of Control Sciences of the Russian Academy of Sciences, Moscow, Russia

    Vladimir M. Vishnevskiy

  2. RUDN University, Moscow, Russia

    Konstantin E. Samouylov

  3. Institute of Control Sciences of the Russian Academy of Sciences, Moscow, Russia

    Dmitry V. Kozyrev

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Vladimirov, S., Vishnevsky, V., Larionov, A., Kirichek, R. (2020). The Model of WBAN Data Acquisition Network Based on UFP. In: Vishnevskiy, V.M., Samouylov, K.E., Kozyrev, D.V. (eds) Distributed Computer and Communication Networks. DCCN 2020. Lecture Notes in Computer Science(), vol 12563. Springer, Cham. https://doi.org/10.1007/978-3-030-66471-8_18

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  • DOI: https://doi.org/10.1007/978-3-030-66471-8_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-66470-1

  • Online ISBN: 978-3-030-66471-8

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