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Scheduling Real-Time Traffic in Underwater Acoustic Wireless Sensor Networks

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Ubiquitous Computing and Ambient Intelligence (IWAAL 2016, AmIHEALTH 2016, UCAmI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10070))

Abstract

Underwater sensor networks are an important field of research. Several applications require the use of this kind of networks like tsunami or oil spill alerts. The underwater medium is very harsh and only acoustic signals can be used for the transmission of information. The use of this kind of networks is still in a developing state far from reaching standard consensus on basic aspects like carrier frequency or modulation techniques. The use of these networks for real-time applications has not been analyzed previously. In this paper we present two solutions for the scheduling of real-time messages and we provide a time constraint analysis of the performance of the network.

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Acknowledgments

This work has been partially supported by the Spanish Ministry of Science and Innovation (MCI) and FEDER funds of the EU under contracts TIN2013-44375-R, TIN2013-47245-C2-1-R and TIN2013-47245-C2-2-R, and also CONFINE project: FP7-288535.

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Authors and Affiliations

  1. Department of Electrical Engineering and Computers, IIIE, UNS-CONICET, Bahía Blanca, Argentina

    Rodrigo Santos, Javier Orozco & Matías Micheletto

  2. Computer Science Department, Universidad de Chile, Santiago, Chile

    Sergio F. Ochoa

  3. Department of Computer Architecture, Universidad Politécnica de Catalunya, Barcelona, Spain

    Roc Meseguer

  4. Department of Computer Engineering, Universitat Rovira i Virgili, Tarragona, Spain

    Pere Millan & Carlos Molina

Authors
  1. Rodrigo Santos
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  2. Javier Orozco
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  3. Matías Micheletto
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  4. Sergio F. Ochoa
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  5. Roc Meseguer
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  6. Pere Millan
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  7. Carlos Molina
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Corresponding author

Correspondence to Rodrigo Santos .

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Editors and Affiliations

  1. University of Las Palmas de Gran Canaria, Las Palmas, Spain

    Carmelo R. García

  2. Departamento de Estadistica, Universidad La Laguna, La Laguna, Spain

    Pino Caballero-Gil

  3. Florida State University, Tallahassee, Florida, USA

    Mike Burmester

  4. University of Las Palmas de Gran Canaria, Las Palmas, Spain

    Alexis Quesada-Arencibia

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Santos, R. et al. (2016). Scheduling Real-Time Traffic in Underwater Acoustic Wireless Sensor Networks. In: García, C., Caballero-Gil, P., Burmester, M., Quesada-Arencibia, A. (eds) Ubiquitous Computing and Ambient Intelligence. IWAAL AmIHEALTH UCAmI 2016 2016 2016. Lecture Notes in Computer Science(), vol 10070. Springer, Cham. https://doi.org/10.1007/978-3-319-48799-1_19

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  • DOI: https://doi.org/10.1007/978-3-319-48799-1_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48798-4

  • Online ISBN: 978-3-319-48799-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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