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Data Aggregation and Forwarding Route Control for Efficient Data Gathering in Dense Mobile Wireless Sensor Networks

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Modeling and Processing for Next-Generation Big-Data Technologies

Part of the book series: Modeling and Optimization in Science and Technologies ((MOST,volume 4))

Abstract

This chapter presents a data gathering method considering geographical distribution of data values for reducing traffic in dense mobile wireless sensor networks. First, we present our previous method (DGUMA) which is a data gathering method that efficiently gathers sensor data using mobile agents in dense mobile wireless sensor networks. Second, we introduce an extended method of DGUMA, named DGUMA/DA (DGUMA with Data Aggregation), that exploits geographical distribution of data values in order to further reduce traffic. Finally, we analyze DGUMA/DA and confirm the effectiveness of the method through some simulation experiments.

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Authors and Affiliations

  1. Osaka University, 1-5 Yamadaoka, Suita, Osaka, Japan

    Kazuya Matsuo, Keisuke Goto, Akimitsu Kanzaki, Takahiro Hara & Shojiro Nishio

Authors
  1. Kazuya Matsuo
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  2. Keisuke Goto
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  3. Akimitsu Kanzaki
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  4. Takahiro Hara
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  5. Shojiro Nishio
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Corresponding author

Correspondence to Kazuya Matsuo .

Editor information

Editors and Affiliations

  1. Universitat Politècnica de Catalunya, Barcelona, Spain

    Fatos Xhafa

  2. Fukuoka Institute of Technology (FIT), Fukuoka, Fukuoka, Japan

    Leonard Barolli

  3. University of Salerno, Salerno, Italy

    Admir Barolli

  4. Canadian Institute of Technology, Tirana, Albania

    Petraq Papajorgji

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Matsuo, K., Goto, K., Kanzaki, A., Hara, T., Nishio, S. (2015). Data Aggregation and Forwarding Route Control for Efficient Data Gathering in Dense Mobile Wireless Sensor Networks. In: Xhafa, F., Barolli, L., Barolli, A., Papajorgji, P. (eds) Modeling and Processing for Next-Generation Big-Data Technologies. Modeling and Optimization in Science and Technologies, vol 4. Springer, Cham. https://doi.org/10.1007/978-3-319-09177-8_5

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  • DOI: https://doi.org/10.1007/978-3-319-09177-8_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09176-1

  • Online ISBN: 978-3-319-09177-8

  • eBook Packages: EngineeringEngineering (R0)

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